Technical Product Manager, App-Layer AI - Hybrid (Lake Oswego, OR)

Elios AI; Lake Oswego (OR); Hybrid; USD 100,000 - 130,000; Full time

Job summary

Elios AI is seeking a Technical Product Manager to lead the integration of AI into user workflows. This hybrid position in Lake Oswego, OR demands over 5 years of product management experience.

The role involves defining AI-powered experiences, setting measurable success criteria, and collaborating with cross-functional teams to drive product value. Candidates should have a strong background in AI product management and the ability to ensure compliance in the use of AI tools.

Qualifications

• 5+ years of product management experience, including AI-enabled products.
• Experience with driving adoption through controlled rollouts and beta programs.
• Ability to define workflows and measurable ROI for intelligent features.

Responsibilities

• Define and execute the roadmap for AI-powered experiences across product applications.
• Identify high-impact opportunities and set measurable success criteria.
• Collaborate with UX, engineering, and application teams to ensure delivery aligns with application roadmap.

Skills

Product Management

AI Product Management

Collaboration

Telemetry and Analytics

User Experience (UX)

Human-in-the-Loop

Beta Program Management

AI Governance

Job description

Technical Product Manager, App-Layer AI - Hybrid (Lake Oswego, OR)

Workplace Type Hybrid

Position Type Permanent

Sector Technology

Skills

• Product Management
• AI Product Management
• Agentic Workflows
• Human-in-the-Loop
• AI Governance
• Product Adoption
• UX
• Collaboration
• Telemetry and Analytics
• Beta Program Management
• GRC Domain

Job Description

Technical Product Manager

Location: Hybrid, based in Lake Oswego, OR or Charlotte, NC | Type: Full Time, Exempt | Experience: 5+ years

About the Role

We're hiring a Technical Product Manager to own how AI shows up inside the product, specifically the AI-powered and agent-assisted experiences embedded directly in user workflows. You'll measure success by adoption and workflow impact, not feature count, and you'll be the person making sure AI lands meaningfully where people actually work.

Our client is a governance, risk, and compliance software company whose tools help large organizations operate ethically and keep their people safe. In this role, you'll translate real compliance and risk workflows into AI-assisted experiences that stay advisory, explainable, and firmly under human control, while still moving fast enough to matter.

What You'll Do

• Define and execute the roadmap for AI-powered experiences across the product applications.
• Turn shared platform AI capabilities into persona-specific workflow value, within governance standards and expansion gates.
• Identify high-impact opportunities and set measurable success criteria, including adoption, workflow acceleration, and quality outcomes.
• Define expansion-readiness thresholds for scaling AI capabilities across products and tenants.
• Partner with platform product management to turn workflow needs into reusable capabilities.
• Translate platform primitives into structured user stories, acceptance criteria, and UX requirements, keeping AI experiences advisory and within human authority boundaries.
• Use telemetry and user feedback to refine experiences and improve trust, usability, and effectiveness.
• Collaborate with UX, engineering, and application teams to align AI delivery with the broader application roadmap.

Qualifications

• 5+ years of product management experience, including AI-enabled, analytics, or data-driven products.
• Demonstrated success driving adoption through controlled rollouts and beta programs.
• Ability to define persona workflows and measurable ROI for intelligent or automation-assisted features.
• Literacy in multi-step agentic workflows, tool-using systems, and human-in-the-loop interaction patterns.
• Working knowledge of AI governance principles, enough to ensure workflow-level compliance and appropriate human oversight.
• Experience translating AI capabilities into structured user stories and acceptance criteria.
• Strong cross-functional collaboration across engineering, design, data science, and domain experts.
• Excellent stakeholder communication, including managing expectations in evolving AI contexts.