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Ai Risk Manager Jobs in Portland, OR (NOW HIRING)

Physical AI Senior Manager

Portland, OR

$134K - $177K/yr

Influence pursuits and proposals: support scoping, estimating, staffing, risk and assumption ... Physical AI Senior Manager - Manufacturing & Supply Chain We are a team of strategic advisors ...

Technical Program Manager

Portland, OR · Remote

$136K - $177K/yr

Position Summary Join Deloitte's AI & Engineering practice to support Technical Program Management ... Lead program governance, risk management, and escalation frameworks across multi-million-dollar ...

Lead tax risk management activities, audits, examinations, and tax controversy matters * Scale and ... AI Readiness. Curiosity and willingness to use AI and emerging technologies to elevate your work ...

IT Manager

Portland, OR · On-site

$70K - $116K/yr

Champion and lead the implementation of AI and emerging technologies with a focus on practical ... CorVel Careers | Opportunities in Risk Management In general, our opportunities will be posted for ...

IT Manager

Portland, OR · Remote

$70K - $116K/yr

Champion and lead the implementation of AI and emerging technologies with a focus on practical ... CorVel Careers | Opportunities in Risk Management In general, our opportunities will be posted for ...

IT Manager

Portland, OR · Remote

$70K - $116K/yr

Champion and lead the implementation of AI and emerging technologies with a focus on practical ... CorVel Careers | Opportunities in Risk Management In general, our opportunities will be posted for ...

AI Solutions and Adoption Lead

Vancouver, WA · On-site

$174K/yr

Prioritize use cases based on business value, feasibility, data readiness, user adoption, and risk ... Work with technical teams to support integrations with CRM, ERP, ticketing systems, knowledge bases ...

AI Solutions Architect

Portland, OR · On-site

$66.75 - $88/hr

Deloitte is focused on helping organizations manage and sustain their performance through their ... risk identification, ethical AI considerations, continuous improvement, and mentoring junior team ...

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Showing results 1-20

Ai Risk Manager information

See Portland, OR salary details

$54.6K

$118.3K

$180.3K

How much do ai risk manager jobs pay per year?

As of Jun 28, 2026, the average yearly pay for ai risk manager in Portland, OR is $118,306.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,400.00 and $136,800.00 per year, depending on experience, location, and employer.

What is the difference between Ai Risk Manager vs Data Scientist?

AspectAi Risk ManagerData Scientist
Required CredentialsTypically requires a degree in risk management, AI, or related fields; certifications in AI or risk management are commonRequires a degree in computer science, statistics, or related fields; certifications in data analysis or machine learning are common
Work EnvironmentWorks in financial, insurance, or tech industries focusing on AI risk assessment and mitigationWorks across industries analyzing data, building models, and deriving insights
Employer & Industry UsageUsed by organizations managing AI deployment risks, especially in regulated sectorsUsed by companies developing AI solutions, data-driven products, and analytics teams

The main difference is that an Ai Risk Manager focuses on identifying and mitigating risks associated with AI systems, often requiring knowledge of risk management and AI ethics. In contrast, a Data Scientist primarily analyzes data and builds models to extract insights, with less emphasis on risk mitigation. Both roles may overlap in AI projects but serve distinct functions within organizations.

What are popular job titles related to Ai Risk Manager jobs in Portland, OR? For Ai Risk Manager jobs in Portland, OR, the most frequently searched job titles are:
What cities near Portland, OR are hiring for Ai Risk Manager jobs? Cities near Portland, OR with the most Ai Risk Manager job openings:
Physical AI Senior Manager

Physical AI Senior Manager

Deloitte

Portland, OR

$134K - $177K/yr

Other

Posted 23 days ago


Deloitte rating

8.0

Company rating: 8.0 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

55th of 139 rated financial services


Job description

Physical AI Senior Manager - Manufacturing & Supply Chain

We are a team of strategic advisors, architects, and implementers who drive business transformations. Our diverse talent energizes clients' business functions and technology to maximize value in Supply Chain enhancing their ability to fulfill their growth and efficiency ambitions. Imagine working with world-class supply network capabilities like Smart Factory, Strategy & Innovation, Supply Chain Responsiveness, Sourcing & Procurement, or Product Development & Operations!
Are you ready to take your career to new heights? Join our US Supply Chain & Network Operations Offering, where you'll deliver transformational solutions using operational expertise, digital technologies, advanced analytics, and industry-specific hybrid solutions. Don't miss the chance to be part of a team that provides exceptional client value while advancing your professional journey. Apply now and become a vital part of our innovative and dynamic workforce!

Recruiting for this role ends on 8/31/26.

The team

You will join a cross-functional Supply Chain & Manufacturing consulting environment focused on helping clients modernize operations through technology, data, and advanced engineering. The role operates in a matrix of industry practitioners, technologists, and alliance partners and requires strong collaboration, structured problem-solving, and the ability to translate emerging technology into operational results.

Work you'll do

You will serve as the functional and domain expert for Physical AI-where AI meets the physical world-across manufacturing and supply chain operations. You will shape advisory engagements, lead proofs of concept (PoCs), and drive implementation programs that combine robotics, computer vision, simulation, digital twins, synthetic data, and edge AI, frequently in partnership with ecosystem alliance providers (e.g., NVIDIA, Siemens, AWS and others). Candidates should be comfortable in factories, warehouses, and leadership conference rooms with the experience to translate between controls engineers, data scientists, and frontline operations.

Key responsibilities
  • Lead Physical AI strategy and advisory for manufacturing and supply chain clients. Identify high-value use cases (e.g., quality inspection, safety, intralogistics, material handling, asset monitoring, autonomous operations), define value hypotheses, and translate to roadmaps and business cases.
  • Own solution shaping and end-to-end architecture spanning sensors, vision, data pipelines, model development, simulation, edge deployment, and operations (i.e., MLOps and ModelOps), with explicit acceptance criteria for operational environments.
  • Drive PoCs and pilots to measurable outcomes. Define experiments, data collection plans, synthetic data approaches (when appropriate), evaluation metrics, and scale plans from pilot-to-plant and factory/network rollout.
  • Integrate AI with real-world constraints: latency, reliability, safety, OT/IT connectivity, cybersecurity, model drift, human-in-the-loop workflows, and maintenance/operating model considerations.
  • Partner with alliances and product teams to translate partner platforms into client-ready reference architectures, demos, and repeatable delivery assets.
  • Influence pursuits and proposals: support scoping, estimating, staffing, risk and assumption framing, and executive-level storytelling. Serve as technical authority in client workshops and due diligence.
  • Lead and mentor multi-disciplinary teams: data science, ML engineering, software and edge, vision, robotics and controls, manufacturing experts, and contribute to capability-building and market activation.

The team

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 10+ years of relevant experience, including client leadership, team leadership, and sustained contribution to business development/pursuits.
  • Experience in at least two of the following domains: 
    • Computer vision for industrial environments (e.g., inspection, defect detection, safety, tracking, manufacturing assembly)
    • Robotics and autonomy (e.g., industrial robotics, mobile robotics and AMRs, perception-to-action workflows)
    • Simulation, digital twins, physics-based modeling for factories, lines, cells, warehousing, and logistics (e.g., discrete event, physics, MILP)
    • Synthetic data generation and validation approaches for model development
    • Edge AI deployment (e.g., performance, reliability, lifecycle operations)
  • Manufacturing and supply chain domain experience in areas such as discrete or process manufacturing, quality systems, maintenance and reliability, intralogistics, warehouse operations, plant OT/IT constraints, safety, and compliance.
  • Ability to travel up to 50%, based on the work you do and the clients and industries/sectors you serve
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

  • Experience collaborating with technology partners (e.g., NVIDIA, Siemens, AWS. and/or similar ecosystems) to translate platforms into deliverable architectures and programs.
  • Manufacturing and supply chain technology exposure in areas such as sensing and IIoT connectivity, process and product optimization, automation and process control, fleet operations, machine learning and data science, cybersecurity for OT
  • Demonstrated experience leading client-facing advisory, PoCs, and implementations (not just research), including requirements, acceptance criteria, and operational handover.
  • Graduate degree (MS/PhD) in Robotics, Computer Science, Electrical/Mechanical Engineering, Industrial Engineering, Applied Physics, Operations Research, or related field.
  • Hands-on experience with NVIDIA ecosystem elements relevant to Physical AI (e.g., accelerated computing for vision/AI at the edge, simulation workflows, robotics stacks) and Siemens engineering platforms and tooling; ability to compare and compose with other vendor stacks.
  • Experience designing governance and operating models for Physical AI in production: model monitoring and drift, incident response, data management, human-in-the-loop, safety and controls integration.
  • Demonstrated thought leadership: reusable accelerators, reference architectures, demo assets, publications, or enablement delivered to internal/external audiences.
  • Business development contribution (pipeline creation, proposal leadership, account expansion) and executive stakeholder management.

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 $171,600 - $322,900.

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.

Information for applicants with a need for accommodation:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

SCNOFY27

#EPCORE

Qualifications:

Physical AI Senior Manager - Manufacturing & Supply Chain

We are a team of strategic advisors, architects, and implementers who drive business transformations. Our diverse talent energizes clients' business functions and technology to maximize value in Supply Chain enhancing their ability to fulfill their growth and efficiency ambitions. Imagine working with world-class supply network capabilities like Smart Factory, Strategy & Innovation, Supply Chain Responsiveness, Sourcing & Procurement, or Product Development & Operations!
Are you ready to take your career to new heights? Join our US Supply Chain & Network Operations Offering, where you'll deliver transformational solutions using operational expertise, digital technologies, advanced analytics, and industry-specific hybrid solutions. Don't miss the chance to be part of a team that provides exceptional client value while advancing your professional journey. Apply now and become a vital part of our innovative and dynamic workforce!

Recruiting for this role ends on 8/31/26.

The team

You will join a cross-functional Supply Chain & Manufacturing consulting environment focused on helping clients modernize operations through technology, data, and advanced engineering. The role operates in a matrix of industry practitioners, technologists, and alliance partners and requires strong collaboration, structured problem-solving, and the ability to translate emerging technology into operational results.

Work you'll do

You will serve as the functional and domain expert for Physical AI-where AI meets the physical world-across manufacturing and supply chain operations. You will shape advisory engagements, lead proofs of concept (PoCs), and drive implementation programs that combine robotics, computer vision, simulation, digital twins, synthetic data, and edge AI, frequently in partnership with ecosystem alliance providers (e.g., NVIDIA, Siemens, AWS and others). Candidates should be comfortable in factories, warehouses, and leadership conference rooms with the experience to translate between controls engineers, data scientists, and frontline operations.

Key responsibilities
  • Lead Physical AI strategy and advisory for manufacturing and supply chain clients. Identify high-value use cases (e.g., quality inspection, safety, intralogistics, material handling, asset monitoring, autonomous operations), define value hypotheses, and translate to roadmaps and business cases.
  • Own solution shaping and end-to-end architecture spanning sensors, vision, data pipelines, model development, simulation, edge deployment, and operations (i.e., MLOps and ModelOps), with explicit acceptance criteria for operational environments.
  • Drive PoCs and pilots to measurable outcomes. Define experiments, data collection plans, synthetic data approaches (when appropriate), evaluation metrics, and scale plans from pilot-to-plant and factory/network rollout.
  • Integrate AI with real-world constraints: latency, reliability, safety, OT/IT connectivity, cybersecurity, model drift, human-in-the-loop workflows, and maintenance/operating model considerations.
  • Partner with alliances and product teams to translate partner platforms into client-ready reference architectures, demos, and repeatable delivery assets.
  • Influence pursuits and proposals: support scoping, estimating, staffing, risk and assumption framing, and executive-level storytelling. Serve as technical authority in client workshops and due diligence.
  • Lead and mentor multi-disciplinary teams: data science, ML engineering, software and edge, vision, robotics and controls, manufacturing experts, and contribute to capability-building and market activation.

The team

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 10+ years of relevant experience, including client leadership, team leadership, and sustained contribution to business development/pursuits.
  • Experience in at least two of the following domains: 
    • Computer vision for industrial environments (e.g., inspection, defect detection, safety, tracking, manufacturing assembly)
    • Robotics and autonomy (e.g., industrial robotics, mobile robotics and AMRs, perception-to-action workflows)
    • Simulation, digital twins, physics-based modeling for factories, lines, cells, warehousing, and logistics (e.g., discrete event, physics, MILP)
    • Synthetic data generation and validation approaches for model development
    • Edge AI deployment (e.g., performance, reliability, lifecycle operations)
  • Manufacturing and supply chain domain experience in areas such as discrete or process manufacturing, quality systems, maintenance and reliability, intralogistics, warehouse operations, plant OT/IT constraints, safety, and compliance.
  • Ability to travel up to 50%, based on the work you do and the clients and industries/sectors you serve
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

  • Experience collaborating with technology partners (e.g., NVIDIA, Siemens, AWS. and/or similar ecosystems) to translate platforms into deliverable architectures and programs.
  • Manufacturing and supply chain technology exposure in areas such as sensing and IIoT connectivity, process and product optimization, automation and process control, fleet operations, machine learning and data science, cybersecurity for OT
  • Demonstrated experience leading client-facing advisory, PoCs, and implementations (not just research), including requirements, acceptance criteria, and operational handover.
  • Graduate degree (MS/PhD) in Robotics, Computer Science, Electrical/Mechanical Engineering, Industrial Engineering, Applied Physics, Operations Research, or related field.
  • Hands-on experience with NVIDIA ecosystem elements relevant to Physical AI (e.g., accelerated computing for vision/AI at the edge, simulation workflows, robotics stacks) and Siemens engineering platforms and tooling; ability to compare and compose with other vendor stacks.
  • Experience designing governance and operating models for Physical AI in production: model monitoring and drift, incident response, data management, human-in-the-loop, safety and controls integration.
  • Demonstrated thought leadership: reusable accelerators, reference architectures, demo assets, publications, or enablement delivered to internal/external audiences....

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