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Embedded Ai Engineer Jobs in Colorado (NOW HIRING)

This role will work as a forward-deployed AI engineer embedded with business and functional leaders to identify high-value problems, rapidly prototype and deploy practical AI solutions, and help ...

This role will work as a forward-deployed AI engineer embedded with business and functional leaders to identify high-value problems, rapidly prototype and deploy practical AI solutions, and help ...

Computer Vision AI Engineer

Aurora, CO · On-site

$99K - $225K/yr

Computer Vision AI Engineer The Opportunity: Booz Allen is seeking an innovative and experienced AI ... Experience with embedded systems programming in C, C++, or Rust * Experience in GPU programming ...

Computer Vision AI Engineer

Aurora, CO · On-site

$99K - $225K/yr

Computer Vision AI Engineer The Opportunity: Booz Allen is seeking an innovative and experienced AI ... Experience with embedded systems programming in C, C++, or Rust * Experience in GPU programming ...

AI Engineering Lead

Denver, CO · On-site

$147 - $220/hr

Role Summary We are hiring a founding AI Engineer Lead to build and scale AI capabilities from the ... embedded in business workflows, and LLM‑driven applications * Translate business needs into ...

New

AI Engineering Lead

Denver, CO · On-site +1

$105K - $139K/yr

We are hiring a founding AI Engineer Lead to build and scale AI capabilities from the ground up ... embedded in business workflows, and LLM-driven applications • Translate business needs into ...

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Showing results 1-20

Embedded Ai Engineer information

See Colorado salary details

$73.6K

$161.3K

$183K

How much do embedded ai engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for embedded ai engineer in Colorado is $161,285.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,300.00 and $181,900.00 per year, depending on experience, location, and employer.

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What are the key skills and qualifications needed to thrive as an embedded AI engineer?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are popular job titles related to Embedded Ai Engineer jobs in Colorado?

For Embedded Ai Engineer jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Embedded Ai Engineer jobs?

Cities in Colorado with the most Embedded Ai Engineer job openings:

Infographic showing various Embedded Ai Engineer job openings in Colorado as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $161,285 per year, or $77.5 per hour.

Full-time

Re-posted yesterday


Job description

What You'll Do   

The Principal AI Engineer is a senior individual contributor who helps Strive turn AI into real operating leverage across the business. This role will work as a forward-deployed AI engineer embedded with business and functional leaders to identify high-value problems, rapidly prototype and deploy practical AI solutions, and help teams adopt new ways of working enabled by enterprise AI platforms such as Claude Code, Glean, and related tools. 

This role is not accountable for Strive's core product roadmaps. Instead, they will operate horizontally across the company, partnering with teams in clinical operations, corporate functions, care model support, and technology to automate workflows, build internal agents and copilots, improve decision support, and accelerate execution. They will combine strong hands-on AI engineering capability with sound judgment about what is worth building, how to deploy it safely, and how to help others use AI effectively. 

Reporting to the VP, Engineering, this role will also help shape Strive's broader AI enablement strategy by influencing platform and tooling recommendations, establishing repeatable patterns for safe and effective AI deployment, training technical and non-technical users, and serving as an internal evangelist for AI transformation.  

The Day to Day   

  • Partner directly with leaders across business units to identify, prioritize, and sequence high-leverage AI opportunities that reduce manual work, improve speed, and increase quality. 
  • Act as a forward-deployed AI engineer, embedding with teams to understand workflows in detail and translate them into practical automations, copilots, agents, and decision-support tools. 
  • Design, build, and deploy internal AI-enabled solutions using enterprise platforms such as Claude Code, Glean, retrieval-based systems, agentic workflows, and orchestration frameworks. 
  • Create reusable patterns, prompts, skills, templates, runbooks, and reference implementations so successful approaches can be adopted repeatedly; help business teams replace repetitive administrative effort with AI-assisted workflows while preserving the human judgment and relationships that matter most. 
  • Work closely with engineering, data, security, compliance, and clinical stakeholders to ensure AI solutions are safe, governed, maintainable, and appropriate for regulated healthcare environments. 
  • Influence enterprise AI tool selection, evaluation, rollout, and usage standards based on hands-on experience and measurable business impact. 
  • Train and enable both technical and non-technical users on how to use AI tools effectively, responsibly, and with the right expectations for quality, risk, and oversight. 
  • Communicate complex AI concepts clearly to executives, clinicians, operators, and frontline teams, translating technical tradeoffs into plain language and practical decisions. 
  • Measure and communicate the impact of AI deployments using operational, productivity, quality, and user adoption metrics. 
  • Serve as an internal evangelist for AI transformation by leading workshops, demos, and office hours; continuously improve how Strive works with AI by sharing lessons learned and recommending where to invest next. 
  • Meet in person with internal and/or external stakeholders to facilitate team and business priorities/opportunities. Business travel may be required for opportunities to connect with stakeholders and attend Strive-sponsored team events. 

Minimum Qualifications 

  • Bachelor's Degree in computer science, engineering, data science, or a related technical field, or equivalent practical experience. 
  • 8+ years of experience in software engineering, machine learning engineering, data engineering, solutions engineering, or a closely related field. 
  • 2+ years of hands-on experience building and deploying AI-powered systems, including generative AI, retrieval-augmented systems, agentic workflows, or AI-enabled automations. 
  • Demonstrated ability to operate as a senior individual contributor in ambiguous environments, independently driving work from problem framing through deployment and adoption. 
  • Strong software engineering fundamentals with practical experience building production-quality tools, services, or workflows. 
  • Experience partnering directly with business stakeholders to translate operational pain points into technical solutions. 
  • Ability to communicate clearly with both technical and non-technical audiences and to influence without formal authority. 
  • Internet Connectivity - Min Speeds: 3.8Mbps/3.0Mbps (up/down); Latency < 60 ms. 
  • Ability to travel and be onsite to meet business needs. 

Preferred Qualifications 

  • Experience working in healthcare, value-based care, or another regulated environment with meaningful privacy, security, and governance requirements. 
  • Strong hands-on experience with enterprise AI platforms and tools such as Claude Code, Glean, coding assistants, agent frameworks, and workflow orchestration tools. 
  • Experience building internal AI copilots, automation tools, knowledge systems, or agentic applications that support operational or clinical teams. 
  • Strong Python skills and experience with cloud-based data and application workflows, ideally in AWS. 
  • Practical experience with retrieval-augmented generation, prompt and context design, evaluation methods, and guardrails for production AI systems. 
  • Experience operating in a forward-deployed, solutions engineering, field engineering, or internal consulting model where speed, judgment, and stakeholder trust are critical. 
  • Track record of influencing tool standards, implementation patterns, and adoption practices across multiple teams. 
  • Experience designing and delivering training, workshops, or enablement programs for users with a wide range of technical backgrounds. 
  • Experience evaluating AI vendors, tools, and architectures with a pragmatic lens on value, risk, usability, and maintainability. 
  • Familiarity with healthcare data, clinical workflows, and collaboration with compliance, security, and legal stakeholders. 

About You  

  • You have strong judgment about what to build, what not to build, and how to maximize practical value from AI inside a real business. 
  • You are highly hands-on and enjoy turning messy operating problems into working systems that people actually use. 
  • You are energized by working side-by-side with teams, earning trust quickly, and helping others adopt better ways of working. 
  • You are a clear communicator who can move comfortably between engineers, operators, clinicians, and executives. 
  • You are excited by change and bring a bias toward action, experimentation, and continuous improvement. 
  • You are thoughtful about safety, governance, and risk, especially when deploying AI into sensitive workflows and data environments. 
  • You are team-first, low-ego, and motivated by enterprise impact more than ownership boundaries. 
  • You are passionate about helping Strive become an AI-native company. 

Annual Salary Range: $130,000 - $196,000