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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.

Andrew V.
Available Now
Verified in SoftDoesAndrew 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.

Andrew V.
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Andrew 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.

Andrew V.
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Andrew 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.
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Verified in SoftDoesBoris S.
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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.
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Eugene M.Verified in SoftDoes
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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
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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.
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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
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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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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.
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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 Unreal Engine 4 Developers can build

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How to hire a Unreal Engine 4 Developer

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 an Unreal Engine 4 Developer through SoftDoes?

SoftDoes deploys pre vetted senior Unreal Engine 4 Developers within days for most engagement models, because the vetting and technical screening have already been completed before you initiate a request. By contrast, traditional direct hire roles for senior UE4 developers take 5 to 8 weeks in typical markets. For principal level roles requiring shipped AAA multiplayer or console experience, timelines stretch to 14 weeks. The SoftDoes model eliminates the sourcing, screening, and technical evaluation phases that consume most of that calendar time, so you get right talent matched to your tech stack and project needs without the pipeline delay.

What does it cost to hire an Unreal Engine 4 Developer?

Senior Unreal Engine developers with C++ generalist profiles command base salaries of US$130,000 to US$175,000 in U.S. direct hire markets. Principal or engine level programmers with shipped AAA titles see compensation of US$155,000 to US$215,000. Hourly rates for senior unreal developers in the U.S. typically range from US$75 to US$140 per hour, with principal level talent reaching US$140 to US$220 per hour. Hourly rates for Unreal Engine developers overall range from $25 to $150, depending on seniority and region. Blueprints only specialists cost roughly 30% to 40% less than C++ UE4 engineers given the lower technical risk profile. Advanced skills like VR/AR development and multiplayer networking increase developer costs. Hiring remote developers from competitive regions in Eastern Europe or Latin America can reduce rates by 30% to 40% for comparable quality without sacrificing quality of output. SoftDoes structures engagements to optimize cost against your specific project requirements and budget.

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

SoftDoes offers three primary engagement models: full time dedicated hire for persistent UE4 work where long term ownership and IP continuity matter; pod or dedicated team deployment where a small cross functional group operates as an extension of your engineering organization; and contract or sprint augmentation for specific project phases, capacity gaps, or time bound deliverables. Choose based on how persistent your UE4 work will be, your risk tolerance, IP and security requirements, and the speed you need. Each model includes engineering led oversight and the flexibility to scale up or down as your project evolves. For teams building immersive experiences in virtual reality or augmented reality, the pod model often works best because it bundles C++ engine expertise with blueprint scripting and optimization techniques under a single delivery umbrella.

How do you ensure time zone alignment with an Unreal Engine 4 Developer?

SoftDoes is North America focused, and the talent network prioritizes developers in U.S. and neighboring time zones, including Latin America and Canada, to ensure real time collaboration overlap. For roles requiring on site presence or strict overlap windows, SoftDoes matches accordingly during the scoping phase. Fully remote developers in distant time zones are only deployed when the engagement model supports asynchronous communication and when the senior developer has demonstrated the ability to adjust communication rhythms for distributed teams. Time zone alignment is treated as a project requirement, not an afterthought.

How does SoftDoes technically vet an Unreal Engine 4 Developer?

Every developer in the SoftDoes network passes an engineering led vetting process, not an HR keyword screen. The evaluation pipeline includes live problem solving on a real Unreal Engine project with measurable issues (such as profiling a level with game performance problems or debugging replication in a multiplayer map), an architecture review where the candidate critiques existing code and proposes redesigns with explicit trade offs, a communication under pressure simulation covering scenarios like a crash during QA or a tight deadline with competing priorities, and a cross functional culture fit assessment evaluating collaboration with designers, artists, and non technical stakeholders. Candidates must demonstrate C++ proficiency, blueprint scripting capability, familiarity with version control systems, and experience with Unreal Engine profiling tools. A strong portfolio with original work and specific contributions to shipped projects is required. This process filters for developers who can own systems and make architecture decisions, not just write code to spec.

What happens if the Unreal Engine 4 Developer isn't the right fit, or I need to scale up or down?

SoftDoes provides a zero risk replacement guarantee. If a developer does not meet your performance standards, SoftDoes replaces them immediately with no recruitment restart penalty and no sunk cost. You are not locked into a hire that is not working. Scaling is equally flexible: you can add developers as your project enters high intensity phases and reduce headcount when the workload contracts, without the overhead, severance risk, or HR friction of traditional full time hiring. This model is designed for the reality that project needs shift, enabling developers to move in and out of your organization cleanly while engineering led oversight ensures continuity and code quality throughout.

The Executive Guide to Hiring an Unreal Engine 4 Developer

A single bad Unreal Engine 4 hire can stall a product roadmap for months, burn through six figures in wasted salary and rework, and leave your codebase worse than before. This playbook gives you a field tested strategy to define, vet, and onboard top tier Unreal Engine 4 Developer talent, built from lessons learned across dozens of enterprise and game development engagements where the cost of getting it wrong was measured in shipped quarters, not résumé stacks.

What Separates a Senior Unreal Engine 4 Developer from an Order Taker

Operational Realities That Define Senior UE4 Talent

Most job postings describe an Unreal Engine 4 Developer as someone who "knows C++ and Blueprints." That tells you nothing about whether they can own a subsystem, ship under constraints, or keep your codebase from collapsing under its own weight. Here is what senior unreal engine developers actually do every day:

  • Own system architecture decisions. They determine when to use C++ for performance critical systems versus blueprint scripting for rapid prototyping. They design modular gameplay frameworks that support expansion without rewriting core systems. Strong proficiency in C++ is non negotiable for anyone touching engine internals, networking, or rendering pipelines.
  • Profile and optimize across the full stack. GPU, CPU, memory, draw calls, LOD systems, tick rates, network replication in multiplayer games. They identify performance bottlenecks using tools like Unreal Insights, then fix root causes rather than symptoms. Developers optimize games for performance across different devices and multiple platforms, including VR headsets like the HTC Vive.
  • Manage technical debt as a business risk. Legacy blueprint sprawl, deprecated subsystems, custom engine modifications on older UE4 versions: a senior developer triages what to patch, what to rewrite, and what to leave alone. Clean and organized Blueprint architecture is essential for this; without it, compile times balloon and bugs compound.
  • Coordinate across disciplines. They work directly with artists, designers, and technical artists. Testing communication skills is necessary since developers work with non technical teams daily. A senior developer translates design intent into technical implementation and defines data driven workflows that keep production moving.
  • Take features from concept to post launch support. Not just coding. Spec review, prototyping, QA coordination, performance tuning, shipping, and live issue debugging. They own the full lifecycle and accept accountability for outcomes.
  • Identify risks before they become budget line items. Platform certification failures, console vs. mobile vs. VR rendering differences, networking edge cases in distributed systems. Experienced developers flag these during planning, not during QA.

Unreal Engine developers use C++ and Blueprints for game development. They create levels, characters, and gameplay mechanics for games. Knowledge of C++ vs. Blueprint roles can impact project efficiency: the wrong split between the two generates rework that a senior developer avoids by making the right call early.

Financial and Operational Impact of the Right Hire

The business case for investing in a battle tested Unreal Engine 4 Developer is measurable:

  • Technical debt reduction. Refactoring poorly scaled blueprints or monolithic C++ classes has cut crash rates and bug fix windows by 30% to 50% in enterprise engagements, reclaiming thousands of engineering hours per year. One enterprise XR client replaced key blueprints with C++ refactored systems and improved frame rate by roughly 30%, while cutting compile times in their beta pipeline by half.
  • Faster deployment cycles. A senior UE4 programmer sets up build automation, packaging, testing, and performance benchmarking. When architecture supports modularity and feature toggles, lead time per feature drops from weeks to days.
  • Infrastructure and tooling optimization. Proper asset pipelines, version control systems that handle large binaries, and live ops patching pipelines reduce downtime, patch failures, and build queue bottlenecks. Collaborative version control workflows are crucial for team environments operating on complex UE4 projects.
  • Risk mitigation across platforms. Unreal Engine 4 can be used for a variety of project types from VR simulations to multiplayer games to architectural visualization. A developer who has shipped on your target platform prevents costly rework, certification rejection, or title launch delays. Unreal Engine supports VR and AR for immersive experiences, but each platform demands different optimization techniques; a developer without prior experience on your target hardware will learn on your dime.

Pre Search Strategy: What to Lock Down Before You Post a Single Job Description

Map Your Architecture and Technical Debt First

Before you write a job description or call a recruiter, audit your codebase. Where are the real bottlenecks? Is multiplayer replication laggy? Are too many Blueprints causing slow compilation? Is your project stuck on an older UE4 version because of custom engine modifications?

Audit your tooling stack as well: CI/CD pipelines, version control for assets, profiling tools, build servers. If you cannot articulate which specific areas drag down delivery, every "enthusiastic" candidate will look identical on paper, and you will only learn who was wrong after they have been on payroll for three months.

Engine source code familiarity is key for complex game mechanics and for diagnosing issues that surface only under production load. If your project demands this level of depth, your audit should flag it before the search begins.

Define Team Dynamics and Autonomy Level

Decide whether this hire embeds into an existing team with lead engineers and technical architects, or whether they will head a small dedicated team and own large subsystems independently. Autonomy expectations grow with seniority; mismatches cause frustration or turnover within the first quarter.

Determine specialization requirements. Do you need deep C++ engine work, graphical shader expertise, virtual reality or augmented reality optimization, multiplayer networking, or tools development? Hiring for "Unreal all round" and expecting strength everywhere is how you end up with a generalist who ships nothing.

In House FTE vs. Vetted Remote Talent

For enterprise work in regulated industries (healthcare simulation, defense training, architectural visualization), in house FTEs may be required for IP protection, security clearance, or compliance. If you need to scale quickly or augment for a specific project phase, vetted remote talent through an engineering partner eliminates months of recruitment overhead.

The difference between a managed engineering partner and freelance unreal engine developers is accountability. Unmanaged freelancers introduce delivery risk; an engineering led partner provides oversight, contract clarity, hourly accountability, and the flexibility to scale up or down as project needs shift.

Engineering the Ideal Profile, Not a Generic Job Spec

A clear job description helps attract qualified Unreal Engine candidates. To avoid lottery hires, build your profile from four components:

  • Core outcome and mission. Define the business impact this developer must deliver in the first 6 to 12 months. Shipping a VR MVP? Refactoring networking code? Stabilizing a live product? That shapes which variant of "senior" you actually need.
  • Technical stack reality. Specify engine version. State whether you need experience shipping console titles, mobile, VR/XR, or live ops. Hiring requires evaluating C++ proficiency and Blueprint skills; be explicit about whether Blueprints alone suffice or C++ is mandatory. Unreal Engine developers should be familiar with Blueprints for visual scripting, but C++ proficiency is essential for anyone touching performance critical paths. Proficiency in 3D modeling tools like Blender or equivalent is essential if your pipeline requires developers to interface with art assets directly.
  • Decision making authority. Will this developer make architecture decisions, or implement someone else's spec? Senior hires expect input into trade offs. If the role is execution only, you need a different profile.
  • Growth trajectory. Opportunity for mentorship, leadership, or ownership of platform and pipeline components influences retention for senior talent. If you offer none of these, expect shorter tenure.
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The Vetting Framework That Filters Out Resume Inflation

Why Traditional Sourcing Fails for UE4 Roles

Traditional recruiters overindex on keyword matches. Many candidates inflate "Blueprints only" experience as "expert UE4." The term "unreal engine expert" appears on résumés far more often than it appears in shipped products. Prescreening via engineering led talent networks, or through a partner like SoftDoes with a vetted talent network, filters out this noise before it wastes your interview pipeline.

Portfolios should show original work and specific contributions to projects, not team credits on large titles where the candidate's actual scope is unclear. Ask for specific subsystem ownership, architecture decisions made, and trade offs navigated.

Technical Evaluation Pipeline

Trivia questions do not predict engineering performance. Structure your evaluation around observable output:

Live problem solving over algorithm puzzles. Give the candidate a real Unreal project with measurable issues: a level with performance bottlenecks to profile, or a simple multiplayer map with replication problems to diagnose. Practical assessments are effective for evaluating candidates' problem solving skills in a way that mirrors actual production work. Debugging skills should include identifying performance bottlenecks in Unreal Engine using tools like Unreal Insights and the built in profiler in the unreal editor.

Architecture review. Present a portion of your existing codebase or system design and ask for critique. How would they redesign a subsystem? What trade offs would they accept given a tight deadline? Candidates should demonstrate familiarity with Unreal Engine profiling tools and a strong understanding of when to optimize versus when to ship.

Communication under pressure. Simulate a production scenario: a crash during QA, a trade off dispute with art or design, a tight deadline with competing priorities. How do they prioritize? What do they push back on? This reveals whether they can operate in the cross functional reality of game development and enterprise visualization.

Cross functional culture fit. A senior developer must speak both code and creative. Assess collaboration instincts: how have they worked with designers, artists, and non technical stakeholders in past roles?

The First 90 Days: A Ramp Up Plan That Produces Immediate ROI

Define a 30/60/90 day plan with clear milestones before the developer's first day:

Days 1 to 30: Shadow the team, learn your engine version, build pipeline, and existing systems. Ship something small and self contained (a bug fix, a minor feature) to prove capability and surface unknown constraints in your environment.

Days 31 to 60: Own a defined slice of active work. Introduce targeted improvements or refactors. Begin contributing to architecture discussions with data from their first month of observation.

Days 61 to 90: Take responsibility over broader features. Advise on architecture and development process improvements. At this point, you should have a clear signal on long term fit, ownership instincts, and technical ceiling.

Set up access to CI/CD, performance tools, asset storage, and build machines before day one. Assign internal stakeholder contacts. Provide whatever internal documentation exists. Friction in the first two weeks compounds into months of lost productivity.

Interview Signals, Strategic Advantage, and Next Steps

Red Flags vs. Green Flags in Candidate Evaluation

Red flags that predict expensive failures:

  1. Only greenfield experience. If a candidate has never dealt with messy existing code, legacy systems, or refactoring, they will struggle in any production environment with history. Avoiding discussion of past failures is a related warning sign.
  2. Tool obsession without problem solving depth. A candidate who talks about Niagara particle systems or real time ray tracing features but cannot explain when a simpler approach is better, or when to avoid overengineering, is a liability. Unreal Engine supports advanced features like real time ray tracing, but knowing when not to use a feature separates senior talent from junior developers learning on your budget.
  3. Inability to quantify performance trade offs. Vague answers about draw calls, garbage collection, culling, or frame time indicate a developer who has not shipped under real constraints. Senior developers charge more but deliver higher quality work precisely because they understand these trade offs at a granular level.
  4. "Senior" defined only by years or job titles. If a candidate cannot describe the scope of decisions they have owned, the systems they have architected, or the trade offs they have navigated, the title is decorative. A candidate's understanding of their own scope of ownership tells you more than their résumé timeline.

Green flags that predict reliable delivery:

  1. Pragmatic trade off analysis. The candidate demonstrates real decisions made under budget, time, or platform constraints, and can describe outcomes. They understand that unreal engine remains the preferred choice for high quality graphics and AAA fidelity, but they also know when to sacrifice visual ceiling for frame rate stability or broader device support.
  2. System integrity focus. They care about testing, performance regressions, modularity, and build health. They defer tempting feature jumps to ensure maintainability. Multiplayer development requires understanding of networking principles in Unreal Engine; candidates who have shipped multiplayer games can speak to rollback, prediction, and bandwidth trade offs with specifics.
  3. Proactive risk identification. They flag dependencies, scalability limits, and maintainability concerns before those concerns become fire drills. Skilled Unreal Engine developers need deep engine specific knowledge to do this credibly.
  4. Cross disciplinary communication. They describe how they worked with artists, designers, and non engineering stakeholders, not just other engineers. They translate design intent into technical work without losing fidelity in either direction.

The SoftDoes Strategic Advantage

SoftDoes operates as a North America focused custom software engineering and data and AI partner serving clients across the US and Canada. When you need to hire unreal engine 4 developers, the SoftDoes model addresses the specific failure modes outlined in this playbook:

  • Battle tested senior talent only. No junior developers learning on your budget. Every unreal developer in the network has shipped production work and passed engineering led vetting.
  • Engineering led delivery oversight. Technical delivery management from principal level engineers, not HR generalists or unmanaged freelancers. This is the difference between a software engineer who ships and a contractor who disappears.
  • Rapid deployment. Access pre vetted specialists through our talent network in days, not the 5 to 14 weeks typical of traditional hiring cycles for unreal engine developers.
  • Zero risk replacement guarantee. If a developer does not meet performance standards, SoftDoes replaces them immediately. No recruitment restart, no sunk cost spiral. One SaaS visualization vendor used this model; the external developer was replaced twice under guarantee before a long term match was found, saving months of mismatch and unblocking feature delivery.
  • Scalable engagement models. Scale your dedicated team up or down based on project phases and budget cycles without the overhead of full time headcount management.

The global game engine market is projected to reach $8.26 billion by 2030. The demand for unreal engine developers is growing across multiple industries, from gaming to enterprise simulation to architectural visualization. Unreal Engine's active monthly users increased by 23% in a recent reporting period. Competition for the right talent is accelerating. Ideal candidates with multiplayer, console, and VR experience are scarce; studios compete with stock options, equity, and creative IP ownership. A strategic talent partner compresses your time to hire and eliminates the risk of a wrong bet.

Your Next Step

Stop burning weeks on recruitment cycles that produce lottery outcomes. Book a technical discovery session with SoftDoes architects to scope your project requirements, map the ideal UE4 developer profile, and get matched with pre vetted senior talent. The cost of waiting is measured in delayed launches, compounding technical debt, and engineering budget burned on the wrong hire.

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