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Aditya P.
Available Now
Verified in SoftDoesAditya P.
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Andrea M.
Available Now
Verified in SoftDoesAndrea M.
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrii V.
Available Now
Verified in SoftDoesAndrii V.
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Boris S.
Available Now
Verified in SoftDoesBoris S.
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Eugene M.
Available Now
Verified in SoftDoesEugene M.
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Hripsime S.
Available Now
Verified in SoftDoesHripsime S.
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
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Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Mario J.
Available Now
Verified in SoftDoesMario J.
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Raphael O.
Available Now
Verified in SoftDoesRaphael O.
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Santiago G.
Available Now
Verified in SoftDoesSantiago G.
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Thierry M.
Available Now
Verified in SoftDoesThierry M.
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thomas S.
Available Now
Verified in SoftDoesThomas S.
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Tzechung K.
Available Now
Verified in SoftDoesTzechung K.
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

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What our Due Diligence Consultants can build

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How to hire a Due Diligence Consultant

01
BROWSE PROFILESRIGHT NOW

Fill out a short form and see who's on the bench. Real profiles, verified histories.

02
Interview1-3 DAYS

Tell us what you need. We propose two or three candidates from the bench; you interview them directly.

03
OnboardWEEK ONE

Your engineer starts on your project. Contract, payments, and the guarantee run through us.

US VS. THE DATABASE

Time to Start
Talent Quality
Technical Vetting
Flexibility
Operational Overhead
Cost Efficiency
cursor
<SoftDoes>
Time to Start
1-2 weeks
Talent Quality
Senior-only engineers
Technical Vetting
Multi-stage screening
Flexibility
Scale up or down anytime
Operational Overhead
As managed as you want
Cost Efficiency
Competitive, fee-free
Talent Marketplaces
Time to Start
1-3 months
Talent Quality
Mixed experience levels
Technical Vetting
One screen, then gone
Flexibility
Contract restrictions
Operational Overhead
Partially managed
Cost Efficiency
Agency markup
In-House Hiring
Time to Start
2-6 months
Talent Quality
Depends on market
Technical Vetting
Internal responsibility
Flexibility
Long-term commitment
Operational Overhead
Fully internal
Cost Efficiency
Highest total cost

Frequently Asked Questions

Everything you need to know about deploying, scaling, and securing your neural agents with SoftDoes. Can’t find an answer?

How long does it take to hire a Due Diligence Consultant through SoftDoes?

Typical external consultant placements through traditional recruiting channels take two to four weeks for sourcing, vetting, interviews, and contract negotiation. SoftDoes compresses this to one to two weeks for senior consultants because our talent network is pre vetted and ready to deploy. For urgent deals on an accelerated timeframe, we have engaged diligence consultants in under ten business days. The speed advantage comes from maintaining a continuously evaluated pool of senior professionals rather than starting a cold search every time a client needs coverage.

What does it cost to hire a Due Diligence Consultant?

Cost scales with deal size, complexity, and regulatory exposure. For seed stage or lightweight diligence on a single codebase with minimal compliance requirements, expect $15,000 to $40,000. Mid stage or growth round engagements typically run $50,000 to $125,000. Large regulated or enterprise cross border deals with multiple compliance frameworks and extensive infrastructure review range from $250,000 to $400,000 or more. SoftDoes offers flexible engagement models and transparent statements of work so you understand exactly what you are paying for before the diligence process begins. We structure fees to be cost effective relative to the deal value at stake, ensuring the investment in diligence consulting is proportional to the risk it mitigates.

What engagement models are available (dedicated hire, pod, contract)?

SoftDoes offers four primary models. A contract or fractional consultant handles short term, targeted deliverables for a single transaction. A dedicated consultant or embedded specialist works inside your organization or leadership team for deeper, ongoing engagements. A pod model deploys a diligence team covering multiple domains simultaneously: security, architecture, regulatory compliance, and product. Finally, we support seller side diligence where companies being acquired need a defensible, independent due diligence report for corporate buyers or PE firms. Each model is designed to match where you are in the deal lifecycle and how many complex transactions you are running concurrently.

How do you ensure time zone alignment with a Due Diligence Consultant?

We select consultants with overlapping working hours based on your location and define core collaboration hours in the engagement agreement. As a North America focused partner, the majority of our senior talent operates within US and Canadian time zones, eliminating the communication lag that plagues offshore models. For engagements requiring broader coverage, we establish clear deliverable expectations and escalation protocols that account for any time zone differences, ensuring that the diligence process never stalls because someone is asleep when a critical question needs answering.

How does SoftDoes technically vet a Due Diligence Consultant?

Our vetting goes well beyond resume screening. We evaluate past project artifacts and deal experience, including the scale of transactions and whether findings actually impacted deal terms. Candidates complete live technical exercises involving real world scenarios: architecture reviews, risk identification under time pressure, and structured communication of findings to a non technical audience. We check references not just for client satisfaction but for measurable outcomes. Consultants should have independence and objectivity to ensure analytical integrity during due diligence, and our evaluation pipeline is designed to confirm that standard before anyone is presented to a client.

What happens if the Due Diligence Consultant isn't the right fit, or I need to scale up or down?

SoftDoes provides a zero risk replacement guarantee. If a consultant is underperforming or is simply not the right cultural or technical fit, we replace them at no additional cost to you. Engagement terms include checkpoint reviews at defined intervals so misalignment is caught early, not after the damage is done. Scaling up is straightforward: we can add specialists to expand coverage across financial due diligence, legal due diligence, or technical streams as deal complexity evolves. Scaling down is equally simple, with flexible exit clauses that protect your budget without locking you into commitments that no longer match your needs.

The Executive Guide to Hiring a Due Diligence Consultant

A single bad hire in a high stakes engagement does not just waste a fee. It delays your deal, exposes hidden liabilities, and burns credibility with investors or board members who expected answers last week. The right due diligence consultant compresses risk, protects valuation, and gives you a defensible picture of what you are actually buying or selling. This playbook is the field tested strategy to define, vet, and onboard top tier due diligence consultant talent so you stop guessing and start making informed decisions backed by real technical depth.

What Actually Separates High Impact Due Diligence from Expensive Guesswork

The Operational Realities That Define a Senior Diligence Specialist

Most executives think hiring due diligence consultants means finding someone who can review financials, scan a codebase, and produce a report. That is table stakes. A senior diligence expert owns the engagement end to end, defines the risk framework, and stands behind findings that shape purchase price, deal structure, and post merger integration. Due diligence involves examining business transactions before decisions, and the person running that examination needs to operate with independence and objectivity to ensure analytical integrity. Here is what separates senior talent from order takers:

  • Codebase Architecture and Tech Debt Judgment: Evaluating monoliths versus microservices, technical debt maturity, modularity, test coverage, and maintainability. They do not just flag problems; they quantify remediation cost and timeline so corporate buyers and principal investors can model risk.
  • Infrastructure Architecture and Cloud Governance: Reviewing multi cloud accounts, Infrastructure as Code hygiene, cost predictability, vendor lock ins, and scalability ceilings. This is operational due diligence at the infrastructure layer, not a surface level checklist.
  • Security, Regulatory Compliance, and Legal Due Diligence Depth: Assessing vulnerabilities alongside compliance frameworks (SOC 2, HIPAA, PCI DSS, GDPR), incident history, and the possibility of past breaches. Legal due diligence examines contracts and regulatory compliance; your diligence consultant begins this work shoulder to shoulder with legal counsel.
  • Team and Org Evaluation: Mapping key person risk, retention signals, velocity, release management maturity, and the target company's workforce structure. This is diligence human resources work that most consulting firms skip entirely.
  • IP, Licensing, and Ownership Analysis: Surfacing open source licensing liabilities, ownership gaps in proprietary code, third party dependencies, and intellectual property encumbrances. Missing this can destroy valuation overnight.
  • Roadmap Feasibility and Strategic Fit: Aligning technical roadmap with the business plan, estimating runway, and articulating tradeoffs between speed, reliability, and cost. Commercial due diligence evaluates market position and growth prospects, but without this technical layer, growth opportunities remain theoretical.

Industry expertise is critical for due diligence consultants because regulations and market dynamics vary widely. A diligence specialist who has never worked in life sciences or corporate finance will miss sector specific landmines that a veteran spots in the first week.

The Financial and Operational Case for Getting This Right

Inadequate due diligence is not a rounding error. It is a valuation event. Due diligence helps identify risks that can have significant financial impacts, and buyers who skip structured technical diligence routinely face outsized cost overruns after acquisition when the target is software heavy. A strong due diligence team can unlock potential synergies in deals that otherwise stay buried. Here are the concrete ROI vectors:

  • Valuation Accuracy and Deal Protection: Catching licensing violations, IP encumbrance, or undisclosed tech debt early prevents costly surprises that reduce valuations. Technical issues found during investor diligence can reduce valuation significantly for SaaS deals, directly impacting cash flow projections and financial forecasts. Due diligence can inform negotiations and structure key deal terms, including purchase price.
  • Remediation and Tech Debt Cost Avoidance: Identifying areas requiring immediate fix versus long term maintenance can save millions in rebuilds. Quantifying tech debt before close gives you leverage and a clear understanding of what the existing business actually needs.
  • Accelerated Integration and Time to Value: Post merger integration insights provide essential guidance for merging systems and cultures. Better clarity pre transaction allows smoother integration. Due diligence consulting can compress transaction timelines by 70%, turning months of uncertainty into weeks of structured progress.
  • Risk Mitigation and Regulatory Avoidance: In regulated sectors, uncovering compliance gaps upfront avoids fines, breach costs, and legal issues. This applies across financial due diligence, operational due diligence, and legal due diligence streams. Financial Due Diligence reviews a company's financial health, while Operational Due Diligence assesses a business's systems and processes, and ESG Due Diligence assesses environmental and social governance factors.

For smaller deals, tech due diligence engagements often cost between $50,000 and $120,000. For larger or regulated complex transactions, or cross border targets, cost ranges climb to $250,000 to $400,000 or more depending on complexity and compliance needs. Seed stage or lightweight diligence may drop to $15,000 to $40,000 for simpler codebases. The cost of not doing it is almost always higher. Due diligence consulting reduces the probability of loss in transactions, and clients rate due diligence consultants 4.9 out of 5 on average for a reason: the ROI is measurable and immediate.

Laying the Groundwork Before You Start Recruiting

Pressure Test Your Own Technical Reality First

Before you talk to a single candidate, you need to audit the technical constraints that will define who you hire and how deep they need to go. Identify your specific due diligence needs before choosing a firm. The due diligence process typically includes five steps: identifying scope, collecting data from various sources, conducting risk assessment of the gathered data, reporting findings and recommendations to stakeholders, and acting on them. Clarity of scope in due diligence prevents important tasks from being overlooked.

Mapping Architecture Complexity and Debt Exposure

What problem must this hire solve first? Is it scaling microservices? Refactoring a monolith? Modernizing legacy code? Or is it mainly compliance and security debt? If you have multiple repos with mixed languages, legacy branches, and poor CI/CD pipelines, that is a fundamentally different architecture complexity than a single modern stack. This defines cost, candidate seniority, and the depth of detailed analysis your diligence examines. A thorough review of your own environment before engaging outside expertise saves weeks of false starts.

Determining Autonomy and Team Fit

Decide whether the hire will be embedded in your engineering organization or function independently. An embedded specialist works alongside your internal engineering leaders, collaborating daily. A consultant assigned as part of a review pod needs to interact quickly with various teams under tight deadlines. Higher autonomy demands proven leadership, decision authority, and the ability to prioritize findings without hand holding. This is especially relevant for private equity firms and corporate acquirers running multiple deals simultaneously where the diligence team must operate with minimal oversight.

Evaluating Deployment Model Tradeoffs

The deployment model matters more than most executives realize. In house FTE hires increase fixed costs, benefits, and overhead. A freelance due diligence consultant gives you flexibility but introduces management burden and consistency risk. Dedicated remote experts through a vetted talent network offer speed and accountability without the overhead of traditional recruiting. Evaluate what is cost effective for your deal pipeline: if you run one transaction a year, a contract engagement makes sense. If you are a PE firm doing serial acquisitions, a dedicated or pod based model delivers better value creation over time.

Building a Precision Profile Instead of a Generic Job Description

Stop posting generic job specs. Engineer the profile around four essential components:

  • Core Outcome and Mission: What does success look like? Is it avoiding deal breakers, quantifying remediation, enabling an integration roadmap, or reducing risk for principal investors? The mission must map directly to your business outcome: deal closing, valuation preservation, integration speed, or some combination. Due diligence should define clear deliverables to avoid scope ambiguity.
  • Technical Stack Reality: The candidate must have experience matching your technical environment. Languages, frameworks, cloud providers, scale, AI/ML pipelines if relevant, hybrid on prem and cloud systems in regulated industries. A diligence expert in fintech infrastructure is not interchangeable with one who specializes in supply chain platforms. Check the consultant's relevant experience in your industry.
  • Decision Making Authority: Does this consultant need to push findings into deal structure? Escalate issues to board or leadership? Negotiate with the seller? Define whether they own the due diligence report or feed into a broader diligence team. Their ability to signal risk and propose risk mitigation measures tied to commercial terms is what separates a strategic partner from a commodity auditor.
  • Growth Trajectory: If the engagement continues post deal (integration, tech debt paydowns, modernization), the consultant should fit an extending role. Maybe they evolve into an architecture lead or transformation advisor. The best engagements are not momentary audits; they are strategic partnerships that scale with the deal lifecycle.
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Separating Real Expertise from Polished Resumes

A Vetting Framework Forged in Actual Deal Pressure

How Sourcing Actually Works (And Where It Fails)

Traditional recruiters often rely on generic candidates and loose references. They optimize for speed to fill, not quality of judgment. In contrast, tapping into prescreened engineering talent networks gives you candidates who have already been evaluated for seniority, technical depth, and the communication skills required to brief non technical stakeholders. Request testimonials from previous clients to assess credibility. Consulting firms should be evaluated for their specific expertise relevant to clients' industries.

Ask for demonstrated deal experience: number of M&A tech diligence projects, scale (deal size, repo count, compliance exposure), and outcomes. Did their findings adjust the purchase price? Cause a walk away? Lead to integration savings? Track record matters more than credentials. Consultants need to manage project deliverables effectively under tight deadlines, and you will not learn that from a resume.

The Technical Evaluation That Actually Reveals Capability

Do not rely on trivia quizzes or tool name recognition. Your evaluation pipeline should stress test judgment:

  • Live Problem Solving: Present a scenario: "This acquired company has 20 repos, uses multiple languages, has no test coverage, and cloud cost is out of control. How would you approach the risk assessment and plan remediation?" Watch how they structure thinking, not just what tools they name.
  • Architecture Review: Give them a system diagram and ask for red flag identification, scaling bottlenecks, and tradeoff decisions. A senior diligence consultant will spot what a junior misses entirely.
  • Communication Under Pressure: Can they explain complex deficiencies clearly for non technical stakeholders like investors, legal counsel, or board members? This is where most candidates fail. Translating a due diligence report into relevant information for executives is a distinct skill.
  • Cross Functional Culture Fit: Your internal engineering, product, security, and compliance leadership all have stakes. Does the candidate cooperate across functions? Do they respect stakeholder concerns and process? Management consulting veterans sometimes clash with engineering cultures; pure engineers sometimes cannot navigate corporate acquirers' governance expectations.

Ensure the firm adheres to high ethical standards and confidentiality. Evaluate the firm's fee structure for transparency and alignment. Due diligence can involve financial, legal, operational, tax, or technical assessments, and your vetting should confirm the candidate can navigate whichever combination your deal requires.

A 90 Day Ramp Up Plan That Produces Results, Not Excuses

Map out measurable milestones so the consultant delivers value before your deal timeline expires. Consultants provide actionable insights for informed decision making, but only if the engagement is structured for velocity:

  • Days 1 through 30: Scope definition, documentation gathering, initial architecture and codebase walkthrough, identification of low hanging deal blocking issues. The diligence consultant begins building the risk register and flagging anything that could affect financial statements or the target company's financial health. They gather and analyze data from various sources during this phase, completing Step 2 of the due diligence process.
  • Days 31 through 60: Deep analysis of infrastructure, compliance, IP and licensing, and team risks. Draft findings with a preliminary risk register. Begin validation interviews with key stakeholders. Align findings with business goals and surface potential risks that require immediate attention. This is where risk assessment of gathered data happens in earnest, directly supporting the financial audit and market analysis streams.
  • Days 61 through 90: Final deliverable including a detailed due diligence report, executive summary, risk and remediation plan, cost and time estimates, and integration or post transaction roadmap. Sign off from leadership. Begin handoff to execution or oversight. The diligence report should cover potential synergies, revenue quality, competitive landscape, market position, and growth opportunities with enough depth for private equity firms and corporate buyers to act on.

This protocol catches deal blockers early and ensures you are not paying full fees before seeing senior impact.

Deciding With Confidence: Signals, Advantage, and Next Steps

The Interview Signals That Predict Success or Disaster

Red Flags That Should End the Conversation:

  • Tool Obsession Without Tradeoff Thinking: "I use tool X, Y, Z" but cannot articulate what tradeoffs those tools forced or what they would do differently. This signals a checkbox operator, not a strategic thinker.
  • Inability to Discuss Past Failures: Every experienced diligence expert has stories about near misses, incorrect assumptions, or findings that arrived too late. If they cannot share lessons learned, they either lack experience or lack self awareness. Both are disqualifying.
  • Fixation on Cosmetic Technicalities: Obsessing over library versions or minor code style issues while ignoring system integrity, reliability, and maintainability. This is the hallmark of someone who has never operated under real deal pressure.
  • Over Promising and Guaranteeing Zero Risk: No one can guarantee zero risk. Claims that "everything looks great" before reviewing artifacts signal either incompetence or dishonesty. Due diligence is crucial before mergers and acquisitions precisely because hidden risks always exist.

Green Flags That Signal You Have Found the Right Person:

  • Pragmatic Tradeoff Analysis: They acknowledge where "fast" versus "good" versus "cost" pull in different directions. They quantify rather than hand wave. This is the deep understanding that separates real operators from consultants who rely on frameworks alone.
  • Data and System Integrity Focus: They prioritize defect density, architecture modularity, test coverage, observability, and incident history. They want to review financials and legal documents alongside technical artifacts because they understand how these streams connect.
  • Proactive Risk Identification: They do not wait for you to ask. They point out hidden risks: single person dependencies, outdated or unpatched dependencies, unclear IP ownership, supply chain vulnerabilities in third party code. They help identify hidden risks and opportunities before you even frame the question.
  • Bilingual in Technical and Business Language: They can brief both the engineering team and the boardroom. They translate technical findings into financial impact, deal terms, and investment decisions. This is the neutral assessment capability that PE firms and corporate acquirers pay a premium for.

Why SoftDoes Wins This Engagement

SoftDoes is a North America focused custom software engineering, data, and AI partner serving clients across the US and Canada. When you need to hire enterprise level consultants for due diligence consulting, the difference between SoftDoes and generic consulting firms comes down to four operational realities:

  • Battle Tested Senior Talent: Our diligence consultants have already navigated M&A tech due diligence, legacy modernization, and compliance heavy stacks. They are not learning on your deal.
  • Engineering Led Delivery Oversight: This is not a freelancer marketplace. Every engagement has accountable consultants with governance, reporting, and no gaps. You get structured diligence consulting, not unmanaged outside expertise.
  • Rapid Deployment on an Accelerated Timeframe: Because our talent is pre vetted, we deploy senior consultants in one to two weeks, not the months typical of traditional recruiting cycles. When your deal is on the clock, speed is not optional.
  • Flexibility and Zero Risk Replacement Guarantee: Scale up or down based on deal flow. If a consultant is not the right fit, we replace them at zero risk to you. No sunk costs, no delays, no excuses.

Your Next Move

Stop burning cycles on generic recruiter pipelines and unvetted freelancers. Book a technical discovery session with SoftDoes architects. In that session, we will map your risk exposure, define scope, outline the ideal consultant profile, and give you preliminary cost and timeline estimates. You walk away with a clear action plan whether you hire through us or not.

Due diligence is not overhead. It is the difference between a deal that creates value and one that destroys it. The question is not whether you can afford to do it right. It is whether you can afford not to.

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