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Embedded Ai Engineer Jobs in Portland, OR (NOW HIRING)

Senior Electrical Engineer

Portland, OR · On-site

$130K - $140K/yr

You collaborate with cross-functional teams including electrical, firmware, embedded, mechanical ... Skilled in Altium Designer, Altium 365, Altium Develop, and AI tools surrounding Altium and PCB ...

Vice President, Platform Engineering

Vancouver, WA · On-site

$190K - $245K/yr

... embedded into application software, platforms, pipelines, and engineering workflows. • Lead the data and AI function, responsible for developing and executing a new vision for delivering trusted ...

You will work with internal and external partners to deliver industry-leading embedded solutions ... Proficiency in applying AI Copilot (LLM-based tools) to accelerate ASIC design, verification, and ...

Designing and delivering embedded artificial intelligence (AI) agent capabilities within Oracle ... Bachelor's degree or higher in computer science, information technology, software engineering ...

Showing results 21-40

Embedded Ai Engineer information

See Portland, OR salary details

$74.2K

$162.7K

$184.5K

How much do embedded ai engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for embedded ai engineer in Portland, OR is $162,664.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,500.00 and $183,500.00 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 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 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 are popular job titles related to Embedded Ai Engineer jobs in Portland, OR?

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

What job categories do people searching Embedded Ai Engineer jobs in Portland, OR look for?

The top searched job categories for Embedded Ai Engineer jobs in Portland, OR are:

What cities near Portland, OR are hiring for Embedded Ai Engineer jobs?

Cities near Portland, OR with the most Embedded Ai Engineer job openings:

Infographic showing various Embedded Ai Engineer job openings in Portland, OR as of August 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $162,664 per year, or $78.2 per hour.

Lead Forward Deployed Engineer, Snowflake

Deloitte

Portland, OR

$108K - $143K/yr

Full-time

Re-posted 20 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Lead ServiceNow FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

Our ServiceNow practice develops strategies and implements systems that help organizations build business value and improve performance. Drawing on deep experience solving complex IT and non-IT challenges globally, we guide clients through everything from system replacement to full Enterprise transformation. We partner with COOs, CHROs, CFOs/CPOs, CISOs, CIOs/CTOs, technology executives, and service owners across HR, IT, Customer, Field Service, and Project Portfolio Management to modernize technology delivery and operating models. By focusing on NextGen technologies and evolving service models, we help clients shift from foundational technology delivery to becoming the strategic business partner and catalyst for change that today's operational demands require.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available
  • 10+ years of consulting or relevant industry experience
  • 4+ years of experience overseeing multiple project teams
  • ServiceNow ITSM certification
  • Certified Application Developer (CAD)
  • A minimum of 2 full life cycle ServiceNow ITSM implementations
  • A minimum of 2 ServiceNow upgrade deployments
  • Experience across IT Service Management, Incident Management, Problem Management, Change Management, Release Management, and Root Cause Analysis (RCA)
  • Experience with the ITIL framework
  • 3+ years' experience as an engagement manager
  • Project scoping, estimating, and planning experience
  • Sales experience
  • Experience leading ServiceNow GenAI/agentic transformations (Now Assist, AI Agents) with familiarity governing enterprise AI via ServiceNow AI Control Tower; exposure to Moveworks-based conversational AI a plus
  • Proven ability to lead architecture of enterprise-scale ServiceNow solutions and advise CIOs and technology executives on platform strategy, roadmap, and capability adoption. ServiceNow SDK experience with Claude and/or GitHub is a plus
  • Track record deploying Claude Code-augmented delivery at scale, including agentic workstreams, MCP orchestration, subagent parallelization, and hooks-based guardrails across engagements
  • Experience building reusable Claude Code skill libraries and slash commands for ServiceNow development patterns to accelerate delivery across a practice
  • Experience training and upskilling customer engineering teams on agentic coding best practices
  • Demonstrated ability to quantify and communicate delivery acceleration to executive stakeholders (e.g., runbooks and documentation evidencing reduced delivery time)

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations
  • ServiceNow Certified Master Architect (CMA) or Certified Technical Architect (CTA)
  • 4+ years of experience generating new client business
  • Experience developing client relationships, identifying new opportunities, and shaping follow-on engagements for continuous improvement
  • Business development experience selling 3+ year deals, including offering structure and support for those deals
  • An advanced degree

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $223,700 to $372900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Lead ServiceNow FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

Our ServiceNow practice develops strategies and implements systems that help organizations build business value and improve performance. Drawing on deep experience solving complex IT and non-IT challenges globally, we guide clients through everything from system replacement to full Enterprise transformation. We partner with COOs, CHROs, CFOs/CPOs, CISOs, CIOs/CTOs, technology executives, and service owners across HR, IT, Customer, Field Service, and Project Portfolio Management to modernize technology delivery and operating models. By focusing on NextGen technologies and evolving service models, we help clients shift from foundational technology delivery to becoming the strategic business partner and catalyst for change that today's operational demands require.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available
  • 10+ years of consulting or relevant industry experience
  • 4+ years of experience overseeing multiple project teams
  • ServiceNow ITSM certification
  • Certified Application Developer (CAD)
  • A minimum of 2 full life cycle ServiceNow ITSM implementations
  • A mi...

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