Principal AI Platform TPM at Angi | $190K–$280K

Angi; United States; Remote; USD 190,000 - 280,000; Full time

Job summary

Angi is seeking a Principal AI Platform TPM to lead the vision, strategy, and roadmap for the AI Platform. You will own the end-to-end AI gateway, cost governance, evaluation, and model serving infrastructure, working with product, engineering, and data science teams across Angi.

This remote, US-based role offers a $190k–$280k salary band with equity and year-end bonus potential. Ideal for leaders who thrive on greenfield, high-scale AI infrastructure and cross-functional impact.

Qualifications

• 8+ years of experience in Product Management, with focus on infrastructure or ML/AI platforms.
• Proven track record scaling technical platforms for internal customers.
• Fluency with AI/ML stack: model serving, API gateways, evaluation, and cloud/Kubernetes infra.

Responsibilities

• Own the AI Platform vision, strategy and roadmap for Angi's model and agent workloads.
• Define governance, cost attribution, routing, and guardrails at scale across teams.
• Lead cross-functional collaboration with engineering, data science, and product to drive adoption of the platform.

Skills

Product Management

AI/ML Systems

Platform Infrastructure

Cross-functional Leadership

Tools

LiteLLM

Langfuse

KServe

SageMaker

Bedrock

Ray

Job description

Principal AI Platform TPM at Angi | $190K–$280K — Remote

This is a Principal-level IC role at an established consumer tech company (Angi, formerly Angie's List, a 30-year-old brand with global scale). It sits at the intersection of two of the hottest areas in tech right now: AI/ML platform engineering and product management — a combination that commands top-of-market compensation.

Compensation benchmark: The $190K–$280K band is well above the median for TPM roles nationally (~$160K–$200K at Staff/Principal level) and aligns with FAANG/top-tier tech principal compensation. The addition of equity and a year-end bonus makes total comp potentially $250K–$350K+, which is competitive even against Big Tech.

• End-to-end AI platform ownership (LLM gateways, eval engines, agent governance) — among the most in-demand skills in the industry through 2026 and beyond.
• Cross-functional influence at the Principal level, a critical career lever for Director/VP transitions.
• Cost governance and ROI telemetry for AI — a nascent but rapidly formalizing discipline.

Green flags: Clear ownership scope, well-defined platform mandate, real infrastructure scale, and exposure to cutting-edge AI tooling (LiteLLM, Langfuse, KServe, Bedrock).

Yellow flags: Angi is a mature, mid-size tech company (not a hyper-growth startup), so equity upside is more moderate than early-stage. The AI platform is described as moving "from experiment to production," suggesting some organizational ambiguity remains. Candidates who thrive on greenfield builds with leadership air cover will fit better than those who prefer fully defined scope.

Overall, this is a strong career accelerator for experienced TPMs looking to specialize in the AI infrastructure space.

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:

• Founded in 1995 as Angie's List and rebranded in 2021
• Global company with 9 brands in 8 countries and employees worldwide
• 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.

What you'll do

Product Management

• 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.
• 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.
• 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.
• LLM & ML Serving Infrastructure: Own the production path for 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.
• Cost & ROI Telemetry: Define and instrument the metrics that track platform health as well as business impact to the platform.

Execution and Leadership

• Cross-Functional Partnership: Establish deep partnerships with product engineering, architecture, and data science to drive adoption and ensure the platform reflects how teams actually build and serve models.
• Technical Roadmap Management: Manage a complex platform backlog spanning parallel tracks under real capacity constraints. Make and communicate authoritative sequencing and trade-off decisions with concise, clear communications.
• 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

• 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.
• Proven track record scaling technical platforms from inception through maturity for demanding internal customers.
• 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 engage deeply with engineers and data scientists on architecture trade-offs.
• 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

• 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).
• Experience with prompt management and versioning, LLM fine-tuning, or self-hosted/open-weight model serving in production.
• 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.
• Experience operating a platform across competing tracks and stakeholders, sequencing revenue-critical stabilization work alongside new strategic build-outs.
• Exceptional leadership skills with a history of influencing cross-functional teams without direct authority.
• 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.
• This position will be eligible for a competitive year-end performance bonus & equity package.
• Full medical, dental, and vision package to fit your needs.
• Flexible vacation policy; work hard and take time when you need it.
• Pet discount plans & retirement plan with company match (401K).
• 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.

Is this Principal TPM role at Angi fully remote? Yes, the job posting is tagged #LI-Remote, indicating this is a fully remote position. However, candidates should expect to work within US business hours given the cross-functional collaboration requirements. What is the salary range for this role? The salary band is $190,000–$280,000, commensurate with experience and performance. The role also includes eligibility for a year-end performance bonus and an equity package. What technical background is required for this AI Platform TPM role? You need 8+ years of product management experience, with at least 4 years on infrastructure, platforms, or ML/AI systems. Technical fluency in model serving, API gateways, evaluation frameworks, and cloud/Kubernetes infrastructure is required. What AI tools and frameworks will I work with in this role? The role involves platforms and tools such as LiteLLM, Langfuse, KServe, SageMaker, Bedrock, and Ray, among others, as well as LLM fine-tuning and self-hosted open-weight model serving in production. Does Angi offer equity as part of this compensation package? Yes, the role is eligible for a competitive year-end performance bonus and an equity package, in addition to the base salary range of $190,000–$280,000.

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