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Hire remote Iot Product Manager

Discover developers that match your project requirements.

No exact match for this specialty yet — here are related experts from our network.

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.
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.

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 Iot Product Managers can build

Not sure which engagement model fits?

SoftDoes takes full ownership of delivery, combining project management, engineering, design, and QA into one accountable team focused on successful outcomes.

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How to hire a Iot Product Manager

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 IoT Product Manager through SoftDoes?

Timelines are significantly shorter than traditional full time recruiting. You can expect a shortlist of qualified candidates within a few weeks, with the selected IoT product manager contributing within 30 to 60 days and fully ramped to leading product cycles or delivering components by day 90. The exact timeline depends on domain complexity, including factors like the regulatory environment, hardware specificity, and whether you need expertise in areas like edge AI or data analytics. For comparison, average time to match with an IoT product manager on some platforms is under 24 hours, but SoftDoes prioritizes depth of vetting alongside speed to ensure the match is right for your organization.

What does it cost to hire an IoT Product Manager?

Cost varies based on seniority, domain specialization, location, and engagement model. Senior IoT product managers in the US working in regulated domains typically command six figure salaries plus benefits when hired full time. Engaging through a delivery partner like SoftDoes often provides more predictable cost structures through engagement fees that include support, replacement guarantees, and scaling flexibility. Remember to factor in infrastructure costs as well: test hardware, cloud environments, development tools, travel for manufacturing oversight, and regulatory or certification expenditures. IoT product managers often have 5+ years of experience, and the investment reflects the breadth of technical skills and product management experience required.

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

SoftDoes offers several models to match your stage and needs. You can hire one full time dedicated IoT product manager embedded in your organization for deep alignment and focus. For broader capability, assemble a pod that combines an IoT PM with firmware engineers, hardware partners, and cloud or data engineers, all coordinated through SoftDoes. Fractional or contract engagements are also available for organizations that need senior IoT PM expertise without committing to a full time role immediately. Each model has trade-offs: dedicated hires offer maximum alignment, pods deliver speed and breadth for new products, and contract or fractional engagements provide flexibility and lower initial investment. Many startups and scale-ups begin with a contract engagement and expand as the product gains traction.

How do you ensure time zone alignment with an IoT Product Manager?

For remote or dedicated hires, SoftDoes provides clarity on working hours overlap from the start. As a North America focused partner, our talent pool consists of professionals whose working hours align substantially with US and Canadian business hours. Scheduled collaboration windows are built into every engagement, which is especially important for IoT roles where hardware prototyping, vendor meetings, and shipping timelines are time sensitive. Whether your team operates on Eastern, Central, or Pacific time, the IoT PM's availability is structured to ensure real time communication when it matters.

How does SoftDoes technically vet an IoT Product Manager?

Our vetting process goes well beyond resume review. We evaluate experience shipping hardware products at volume with real field deployments, not just lab prototypes. Candidates are assessed for depth of knowledge across firmware, cloud architecture, connectivity protocols, security, and manufacturability. The process includes technical screening focused on trade-off reasoning, practical exercises simulating real world IoT product challenges, and reference checks specifically targeting hardware production experience, edge reliability, regulatory compliance, and OTA update management. We look for candidates who can demonstrate skills in assessing hardware and software trade-offs during interviews and who can articulate how they have managed dependencies between hardware, firmware, and cloud systems. SoftDoes emphasizes senior level fluency and a proven track record of delivering innovative products, not just keyword matching.

What happens if the IoT Product Manager isn't the right fit, or I need to scale up or down?

SoftDoes provides replacement guarantees and scaling flexibility as part of every engagement. If the IoT PM is not performing or the fit is not right, you can request a replacement without starting a new hiring cycle from scratch. If your product needs evolve, you can scale resources up by adding firmware engineers, hardware specialists, or data engineers to support the PM, or scale down as product phases shift. This flexibility allows you to adjust capacity based on real project demands without the overhead of traditional recruiting or procurement. The goal is to keep your IoT product initiatives moving forward regardless of how your workforce needs change.

How to Hire an Iot Product Manager

Most companies attempting to launch a connected device discover too late that their product manager lacks the cross-domain fluency to coordinate hardware, firmware, cloud, and compliance in parallel. The result: missed production deadlines, blown budgets, and devices that stall after the prototype stage. This guide walks you through what an IoT product manager actually does, how to define the role for your organization, how to source and vet candidates who can deliver, and how partnering with SoftDoes gives you a faster, lower risk path to the right hire.

What an IoT Product Manager Actually Does and Why the Role Keeps Evolving

The Real Day to Day: Core Responsibilities of an IoT Product Manager

An IoT product manager sits at the intersection of hardware engineering, embedded firmware, cloud infrastructure, connectivity, regulatory compliance, and end user experience. Unlike a traditional product manager or even a technical product manager focused purely on software, this role demands fluency across physical and digital systems simultaneously. IoT requires balancing the physical world with the digital world, and the person in this seat is the one who makes that balance work.

Hiring an IoT product manager requires understanding product manager responsibilities unique to IoT. In practice, here is what the role involves day to day:

  • Specifying hardware trade-offs: evaluating component choices for power consumption, cost, durability, and manufacturability, then coordinating with vendors and contract manufacturers to lock specifications early enough to avoid production delays.
  • Aligning firmware with cloud and connectivity: ensuring alignment between embedded software development and cloud architecture across protocols like Wi-Fi, BLE, LoRaWAN, NB-IoT, or cellular, so that devices communicate reliably at scale. Knowledge of various communication protocols is crucial for managing IoT devices.
  • Designing data pipelines and product analytics: defining how device telemetry is collected, transmitted, stored, and processed. IoT generates massive amounts of telemetry data requiring effective data processing strategies, and the PM must own the strategy for turning that data into actionable insight.
  • Owning security and compliance: overseeing encryption on device and in transit, secure boot, OTA update mechanisms, and regulatory compliance (FCC, CE, HIPAA, and regional certifications). NIST emphasizes that IoT security must be considered throughout the product lifecycle, not bolted on after launch.
  • Managing the full device lifecycle: from ideation and prototyping through pilot deployment, production ramp, field support, and end of life planning. Device lifecycle management is essential for IoT due to long-lived devices that may operate for years in harsh environments.
  • Tracking KPIs across hardware and software domains: device reliability uptime, mean time between failures, data quality, latency, power consumption, customer satisfaction, and retention for services running on top of the device.

Successful IoT product managers often have a background in engineering, and many bring 5+ years of product management experience along with Agile and Scrum certifications that help them manage cross-functional teams effectively.

Why Getting This Hire Right Is a Strategic Priority

The difference between a capable IoT PM and a mismatched one shows up directly on your balance sheet and your launch timeline. Here are the concrete business outcomes at stake:

  • Faster time to market: a skilled IoT PM prevents the misalignment between hardware, firmware, cloud, and UX timelines that causes months of delay. They lock hardware specs early, sequence dependencies correctly, and keep cross-functional teams moving in parallel.
  • Controlled costs and healthier margins: early decisions around manufacturability, component sourcing, power draw, and connectivity method directly impact your cost of goods sold. Building a physical device involves managing tooling, manufacturing ramps, and supply chain bottlenecks, and the right PM makes those decisions before they become expensive problems.
  • System reliability that scales: a senior product manager ensures architecture supports growth from pilot to thousands or millions of devices without major rework. This includes edge computing constraints, silicon selection, and data pipeline design.
  • Risk reduction in compliance, security, and privacy: security is critical in IoT due to the risk of cyberattacks targeting connected devices. A qualified IoT PM builds security and regulatory requirements into the product vision from day one, reducing the risk of recalls, fines, and reputational damage.

How to Prepare Internally Before Opening the Role

Defining Your Needs Before You Start Searching

Before posting a job listing or engaging a delivery partner, invest time in internal clarity. The more precisely you define what you need, the faster you will find a match with a candidate who can deliver.

Project Scope and Requirements

Start by articulating the fundamentals of your IoT product. What type of device are you building: industrial, consumer, wearable, medical? What are your target manufacturing volumes? What constraints exist around size, power, and cost? What regulatory environment applies? Do you need OTA updates, remote diagnostics, or edge AI capabilities? Candidates should understand the constraints of edge computing and silicon selection, so your scope definition should be detailed enough that a strong candidate can immediately evaluate feasibility and trade-offs.

Also consider the technology stack: what cloud backend will the product use (AWS IoT, Azure IoT, custom infrastructure)? Will machine learning run on the device or in the cloud? What is the expected device lifetime? These details shape the profile of the IoT product manager you need.

Team Structure and Engagement Model

Map out who the IoT PM will collaborate with: hardware engineers, firmware and embedded developers, cloud and edge software teams, UX/UI designers, security specialists, operations, supply chain, compliance, and legal. Clarify which of these roles are in house and which are external. Define decision rights: who owns hardware specs, who controls the app interface, who signs off on compliance.

Stakeholder management is a critical skill for this role. The PM will need to translate between departments that speak different technical languages, ensuring alignment across teams with very different timelines and priorities.

In House vs. Dedicated Remote Talent

Decide whether you want a full time internal hire or whether you will leverage a delivery partner for access to senior talent. Key trade-offs: an internal hire offers tighter control and deeper organizational integration. Dedicated remote IoT product managers through a partner like SoftDoes provide access to rare senior expertise faster, often with more predictable costs and built in support structures. For many organizations, especially those without an existing IoT product management function, starting with a partner engagement reduces the risk of a costly mis-hire.

Writing a Job Description That Attracts Top IoT Product Managers

A vague job description will attract generic applicants. To reach experienced product manager candidates with real IoT depth, your listing must be specific and compelling. Cover these four elements:

  • Mission: state the core objective of the role in business terms. For example, "Lead the launch of industrial monitoring sensors that reduce customer downtime by 40%" or "Build the connected wearable ecosystem that drives our subscription revenue." The mission signals impact and attracts candidates with a desire to own outcomes, not just features.
  • Stack and context: enumerate the hardware platforms, firmware toolchains, connectivity protocols, cloud providers, deployment environments, and regulatory landscape. This allows top IoT product managers to self-select and demonstrates that your company understands the domain.
  • Team structure: describe reporting lines, cross-functional collaboration expectations, vendor management responsibilities, and the level of authority the PM will have over hardware, firmware, and product design decisions.
  • Growth and impact: outline career development opportunities, the scale of the product initiative (device volumes, new markets, revenue targets), and the resources available, including whether the hire will be supported by a delivery partner like SoftDoes or a dedicated internal team.
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How to Source, Evaluate, and Onboard an IoT Product Manager

Building a Vetting Process That Goes Beyond Resumes

Sourcing Strategy

Experienced IoT product managers are rare. Standard job boards and generalist recruiters often fall short because the role demands a combination of hardware awareness, software fluency, and product management experience that few candidates possess. Start with specialized networks: IoT and embedded systems communities, industry conferences focused on hardware and software convergence, and niche PM groups. Some platforms claim rapid matching (Arc claims to source talent in less than 72 hours, for example), but speed without depth of vetting creates its own risks.

Also consider engineering consultancy partners or custom software development teams that already include senior IoT product management talent. Proactive outreach consistently outperforms inbound applications for this role.

Vetting Beyond the Resume

Resumes list product launches, but titles alone do not confirm fit. IoT products require candidates to balance hardware and software trade-offs and long term device management, so your evaluation process must test for this directly:

  • Technical screening: evaluate the candidate's understanding of hardware constraints, firmware challenges, cloud scaling, connectivity protocols, and power management. Candidates should demonstrate skills in assessing hardware and software trade-offs during interviews. Ask about prioritization under physical constraints, a key skill for IoT product managers.
  • Practical real world task: present a scenario such as designing a connected device for remote monitoring in a rural environment with intermittent connectivity. Ask the candidate to outline trade-offs, identify risks, propose a timeline, and explain how they would handle supply chain bottlenecks. Strong candidates explore systemic interdependencies during product management scenarios rather than isolating problems.
  • Analytical and problem solving interview: have the candidate interpret real telemetry data, perform root cause analysis on a device failure log, or propose a data processing strategy for a fleet of connected devices. Experience in data analysis is crucial for IoT product managers.
  • Culture and communication fit: look for stakeholder management ability, risk awareness, documentation discipline, and the capacity to coordinate across hardware, firmware, and software teams. Strong communication skills matter as much as technical skills here. Understanding customer experience is vital for IoT product managers beyond just technical knowledge.

Two critical red flags to probe for: blame shifting to engineering during product challenges indicates a weak candidate for IoT PM, and treating security as merely an engineering concern rather than a product responsibility signals a gap in IoT maturity.

Candidates should provide examples of taking IoT products from concept to deployment. If they can only talk about prototypes and never about field deployment, manufacturing ramps, or end of life management, that is a significant gap.

Setting Up Your New Hire for Success: The 30/60/90 Day Plan

A structured onboarding plan ensures your IoT PM ramps quickly and stays engaged:

  • First 30 days: immersion in the existing product, customers, data pipelines, regulatory requirements, supply chain partners, and manufacturing relationships. The PM should understand the current state before proposing changes. Prioritize access to hardware test setups, data environments, and vendor contacts.
  • Days 30 to 60: the PM begins leading small feature cycles or improvement initiatives, building or refining the product roadmap, and aligning cross-functional teams. They should start establishing analytics and metrics to track device health and customer usage.
  • Days 60 to 90: by this point, the PM should have shipped an improvement, established a measurement framework, or completed a product initiative that demonstrates value. Ensure regular feedback loops, executive visibility, and clarity of goals.

Retention depends on giving the IoT PM real authority, access to resources, and a clear connection between their work and business outcomes. Top IoT product managers are rated 4.9 out of 5.0 on average across talent platforms, which means they have options. Invest in the relationship.

How to Spot the Right Candidate and Make a Confident Decision

Warning Signs and Positive Indicators During the Interview Process

Red flags to watch for:

  • Claims hardware experience but has only built prototypes, with no involvement in manufacturing, field deployment, or scale production. IoT products require lifecycle thinking from ordering to end of life management.
  • Poor understanding of manufacturing constraints, supply chain risks, or cost of goods. Overpromising on hardware timelines or component costs is a consistent predictor of project failure.
  • Treats IoT like pure software: ignores firmware dependencies, power constraints, connectivity limitations, and environmental durability. IoT product managers must manage dependencies between hardware, firmware, and cloud systems.
  • No awareness of regulatory requirements, security standards, or data privacy obligations. Security should not be treated as merely an engineering concern in IoT management.

Green flags that signal senior capability:

  • A proven track record managing full device lifecycles across hardware, firmware, cloud, and UX, from concept through scaled deployment.
  • Demonstrated trade-off decision making under hardware constraints: power, cost, thermal, connectivity, and form factor.
  • History of moving from pilot or prototype to production deployment, including managing field issues, OTA updates, and iterative improvement.
  • Familiarity with regulated domains or high reliability use cases (medical devices, industrial IoT, energy, agriculture) where uptime and safety are non-negotiable. Candidates should also know how to transition from hardware sales to recurring revenue streams, reflecting modern IoT business models.

Notable examples exist in the industry: Alice has 15 years of experience in product ownership, and Eric Nowak built a $1.2 billion network and security business. These profiles illustrate the caliber of experienced product manager talent that exists for IoT roles when you know where to look.

Why Partnering with SoftDoes Gives You an Edge

SoftDoes is a North America focused software engineering and talent delivery partner serving clients across the US and Canada. Unlike freelancer marketplaces or generalist staffing agencies, SoftDoes operates a team delivery model where professionals take full ownership of outcomes, not just tasks.

Here is what that means for your IoT product manager hire:

  • Pre-vetted senior talent: every IoT PM in our network has been evaluated for technical depth across firmware, cloud, connectivity, security, and manufacturability, not just resume credentials.
  • Team delivery, not isolated contractors: your IoT PM works within a delivery structure that includes engineering support, established workflows, and accountability. This eliminates the vendor management burden that comes with cobbling together freelancers.
  • Replacement and scaling guarantees: if the hire is not the right fit, you can request a replacement without restarting a procurement cycle. Need to add firmware engineers, hardware specialists, or data engineers to support the PM? Scale up or down based on your product initiatives.
  • Flexible engagement models: from a single dedicated IoT product manager to a full pod (PM plus firmware engineer plus cloud and data engineer), SoftDoes adapts to your stage and scope.
  • Deep domain experience in regulated industries: SoftDoes has strong experience in finance, healthcare, and energy, sectors where devices require auditability, data privacy, security, and lifetime support. This industry focus translates directly to IoT product management that accounts for compliance from day one.

Clients rate top IoT product managers 4.9 out of 5.0 on average, and average time to match with an IoT product manager through leading platforms is under 24 hours. SoftDoes combines that speed with the depth of vetting that ensures you are not just getting a fast match but the right one.

Ready to Hire an IoT Product Manager?

If you are building connected devices and need a product owner who can orchestrate hardware, firmware, cloud, and compliance into a successful launch, the next step is straightforward. Schedule a discovery call with SoftDoes to define your IoT product management needs, review pre-vetted candidates, and start building with confidence. No long procurement cycles. No talent lottery. Just a direct path to the senior IoT expertise your product demands.

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