[All remote jobs](https://jobicy.com/jobs.md)[![ANGI logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2021/09/50cccf084c34089de2274f72e18841d0.jpg)](https://jobicy.com/company/angi.md)[ANGI](https://jobicy.com/company/angi.md)

# Principal Product Manager, AI Platform

AI Summary Angi is seeking a Principal Technical Product Manager to define the vision, strategy, and roadmap for a shared AI Platform. The role owns an AI gateway, model routing and cost governance, evaluation gates, prompt lifecycle management, agent trust controls, and production ML/LLM serving. This leader will partner closely with engineering, architecture, and data science teams to drive platform adoption and make high-impact sequencing decisions across parallel initiatives. The position requires deep technical product management experience, fluency with AI infrastructure, and the ability to connect platform investments to measurable business outcomes.[Apply for this job](#job-application)[View company](https://jobicy.com/company/angi.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 190k–280k / yrDepartment[Product & Operations](https://jobicy.com/categories/management.md)EmploymentFull TimeExperienceSeniorPublished5 Nov 2026Apply before5 Dec 2026Listing views16Application actions0Application toolkit

## Make your next move.

Prepare your resume, explore your fit, and draft a cover letter for this opportunity.

Opportunity details

## About this role.

For over 30 years, Angi has powered the future of the home services industry, creating an environment where homeowners and pros benefit from more jobs done well.

For homeowners, our platform is a reliable way to find skilled pros. For pros, we’re a reliable business partner who helps them find the winnable work they want, when they want. For employees, we’re an amazing place to call home. We can’t wait to welcome you.

Angi at a glance:

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Founded in 1995 as Angie’s List and rebranded in 2021

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Global company with 9 brands in 8 countries and employees worldwide

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Homeowners have turned to us for 300 million home projects and counting

### About the team

This Principal Technical Product Manager will own the vision, strategy, and roadmap for the AI Platform: the shared, governed entry point every model and agent workload at Angi runs through. As generative AI moves from experiment to production across the company, this team manages the common platform with routing, cost attribution, quality evaluation, and guardrails built in rather than rebuilt by every team.

The ideal candidate is a technical product manager who treats infrastructure as a product and has a strong thesis on how AI is reshaping the way software and models get built and served. You will own the platform that our product engineering, data science and their associated agents depend on: a model-agnostic AI Gateway, eval-gated prompt management, self-hosted and fine-tuned model serving, and the trust-and-autonomy ladder that governs how much independence each agent earns. Your measure of success is not just adoption and scale, but are we meaningfully improving our products and enabling our internal teams.

### What you’ll do

Product Management

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AI Gateway & Cost Governance: Own the vision for a governed, model-agnostic gateway that all model and agent traffic routes through, with per-team and per-use-case cost attribution, flexible model routing, rate limiting, provider failover, and automatic spending caps and stop switches. Make model-swap and cost decisions changeable once at the gateway, not per service.

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Evaluation & Quality Enforcement: Define the roadmap for the eval engine and the pass/fail gate that runs on it, eval-gated prompt management with versioning and rollback, and per-agent accuracy scoring — so quality regressions are caught before they reach users rather than surfacing downstream in business metrics.

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Trust & Autonomy Ladder: Define and champion the trust-and-autonomy ladder — the thresholds, progression criteria, evidence, approvals, and rollback logic that govern when an agent earns more independence — so agentic adoption scales with accountability instead of governance gaps.

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LLM & ML Serving Infrastructure: Own the production path self-hosted LLM /open-weight model serving and traditional ML with the goal to consolidate both ML and LLM workloads under one standardized observable platform.

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Cost & ROI Telemetry: Define and instrument the metrics that track the platform health as well as business impact to the platform.

Execution And Leadership

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Cross-Functional Partnership: Establish deep partnerships with product engineering, architecture and data science to drive adoption and make sure the platform reflects how teams actually build and serve models.

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Technical Roadmap Management: Manage a complex platform backlog spanning parallel tracks and under real capacity constraints. Make and communicate authoritative sequencing and trade-off decisions with concise and clear communications.

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Stakeholder Communication: Act as the primary interface between technical platform teams and business stakeholders, translating infrastructure investment into clear business outcomes

### Who you are

Minimum Qualifications

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8+ years of experience in Product Management, with at least 4 years focused on infrastructure, platforms, ML/AI systems, or other technical products serving internal engineering or data-science customers.

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Proven track record scaling technical platforms from inception through maturity for demanding internal customers.

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Technical fluency across the modern AI/ML stack — model serving and inference, API gateways/proxies, evaluation and testing frameworks, and cloud/Kubernetes infrastructure — sufficient to “swim with the fishes” with engineers and data scientists on architecture trade-offs.

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Demonstrated ability to use telemetry and cost data (model performance, eval results, adoption analytics, spend data) to diagnose bottlenecks and drive product strategy.

Preferred Qualifications

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Hands-on familiarity with LLM gateways/proxies (e.g., LiteLLM), evaluation and observability tooling (e.g., Langfuse), and model serving frameworks (e.g., KServe, SageMaker, Bedrock, Ray).

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Experience with prompt management and versioning, LLM fine-tuning, or self-hosted/open-weight model serving in production.

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Familiarity with agent governance concepts — guardrails, PII controls, prompt-injection protection, and autonomy/trust frameworks — and with the tension between agent velocity and cost control.

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Experience operating a platform across competing tracks and stakeholders, sequencing revenue-critical stabilization work alongside a new strategic build-out.

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Exceptional leadership skills with a history of influencing cross-functional teams without direct authority.

Compensation & Benefits

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The salary band for this position ranges from $190,000 – $280,000 commensurate with experience and performance. Compensation may vary based on factors such as geographic location.

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This position will be eligible for a competitive year end performance bonus & equity package.

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Full medical, dental, vision package to fit your needs

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Flexible vacation policy; work hard and take time when you need it

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Pet discount plans & retirement plan with company match (401K)

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The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world

We value diversity. We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.

Our hiring process may utilize artificial intelligence (AI) tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.

#LI-Remote

Show more

[Apply now >](https://jobicy.com/jobs/159139-principal-product-manager-ai-platform.md)

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## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a principal-level platform product role covering complex AI infrastructure, governance, reliability, cost controls, and cross-functional prioritization. Success requires influencing senior technical stakeholders while making consequential architecture and roadmap trade-offs.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Highly competitive$235,000US market range (per year)$190k–$280k0$308k

AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of $190,000–$280,000 USD. The annual cadence is inferred from the magnitude of the US-based full-time professional salary band because the posting does not explicitly state a pay period. A midpoint estimate is $235,000 per year; the stated range is consistent with the estimated US market range for a principal AI platform product management role.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Technical Product Management](https://jobicy.com/jobs?search_keywords=Technical%20Product%20Management.md)[AI Platform Strategy](https://jobicy.com/jobs?search_keywords=AI%20Platform%20Strategy.md)[LLM Infrastructure](https://jobicy.com/jobs?search_keywords=LLM%20Infrastructure.md)[ML Model Serving](https://jobicy.com/jobs?search_keywords=ML%20Model%20Serving.md)[API Gateways](https://jobicy.com/jobs?search_keywords=API%20Gateways.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[Product Roadmapping](https://jobicy.com/jobs?search_keywords=Product%20Roadmapping.md)[Cost Governance](https://jobicy.com/jobs?search_keywords=Cost%20Governance.md)[AI Evaluation Frameworks](https://jobicy.com/jobs?search_keywords=AI%20Evaluation%20Frameworks.md)[Prompt Management](https://jobicy.com/jobs?search_keywords=Prompt%20Management.md)[Agent Governance](https://jobicy.com/jobs?search_keywords=Agent%20Governance.md)[Telemetry and Analytics](https://jobicy.com/jobs?search_keywords=Telemetry%20and%20Analytics.md)[Stakeholder Management](https://jobicy.com/jobs?search_keywords=Stakeholder%20Management.md)[Cross-functional Leadership](https://jobicy.com/jobs?search_keywords=Cross-functional%20Leadership.md)

Sample interview questionsHow would you prioritize the initial roadmap for a shared AI platform used by multiple engineering and data-science teams?I would begin with discovery across user groups, production workloads, reliability risks, and spend patterns. I would prioritize foundational capabilities that reduce repeated work and operational risk, such as a governed gateway, observability, cost attribution, and evaluation controls, then sequence higher-level self-service and agent capabilities based on adoption and measurable impact.

How would you measure whether an AI gateway is creating value for internal teams?

I would track adoption by team and workload, request reliability, latency, model quality, provider failover success, unit cost, and the percentage of traffic governed through the gateway. I would pair these operational metrics with outcome measures such as delivery speed, reduced duplicated integrations, avoided spend, and improvements in customer-facing product quality.

Describe an approach to implementing evaluation-gated prompt management in production.

I would establish versioned prompts, representative evaluation datasets, quality thresholds, and automated checks within the release workflow. New prompt versions would move through offline evaluation and controlled rollout stages, with monitoring, rollback capabilities, and clear ownership for exceptions or threshold changes.

How would you balance rapid agent deployment with governance and safety requirements?

I would use a tiered trust-and-autonomy model in which agents earn broader permissions through demonstrated performance, auditability, and safe operational behavior. Each level would define required evidence, human approvals, guardrails, PII controls, rollback paths, and monitoring so teams can move quickly without creating unmanaged risk.

Tell us about a time you had to make a difficult platform trade-off under capacity constraints.

I would explain the customer and business impact of each option, quantify risks and dependencies, and align stakeholders on decision criteria such as reliability, revenue impact, cost, and strategic leverage. I would document the sequencing decision, communicate what is deferred and why, and use leading indicators to revisit the choice if conditions change.

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