Model Operations Lead, AI Gateway

Cloudflare•Austin, TX

13d•$230,000 - $317,000

About The Position

Cloudflare is hiring a people manager to build and lead the models team for AI Gateway. The team helps developers understand whether models perform as described and which models are best suited to their needs. The role initially focuses on model operations, including provider integrations, capability testing, pricing and metering, capacity, security reviews, documentation, health, and deprecations. It also develops model intelligence from AI Gateway traffic, including capability maps, per-task rankings, auto-routing profiles, evaluations, regression detection, and market intelligence. The lead will hire, develop, and manage the team while remaining hands-on with code, agent-driven workflows, launches, and evaluations. They will oversee model launches from scope through testing, pricing, security, documentation, and announcements; maintain an accurate and reliable catalog; and make evidence-based decisions about catalog contents and routing recommendations. The role also establishes a lightweight operating cadence, coordinates stakeholders and providers, and automates recurring launch and evaluation work. It reports to the AI Gateway Engineering Manager. The position is available in Austin, Texas; New York City, New York; and San Francisco, California. Compensation varies by location. The role is eligible for Cloudflare’s equity plan.

Requirements

Experience hiring, managing, and growing engineers or operators; providing direct feedback, delegating meaningful ownership, and developing team members.
A proven track record of taking technical launches or integrations from ambiguity to production across teams and partners.
Hands-on ability to write TypeScript, Python, or Rust; read API documentation; inspect endpoints; and debug with terminal tools such as logs and cURL.
Deep familiarity with new models, model labs, and inference providers.
Hands-on understanding of streaming, tool calling, structured outputs, rate limits, token pricing, and provider-specific model behavior.
Data-driven product judgment for adding, modifying, or retiring catalog items.
An SRE approach to defining, measuring, and alerting on service health, managing incidents calmly, and fixing root causes.
Daily experience building with agents, including scoping work, verifying outputs, and applying deterministic checks or human judgment appropriately.
Meticulous attention to model IDs, context limits, per-token prices, and response fields.

Nice To Haves

Experience at an inference provider, model lab, model router, evaluation platform, or API company.
Background in evaluations, ranking or recommendation systems, observability, metering, or usage-based billing.
Familiarity with Cloudflare Workers, AI Gateway, Workers AI, or Replicate.
Relevant experience in engineering management, SRE, partner engineering, evaluations or applied ML, technical program management, or solutions engineering.

Responsibilities

Hire, coach, and develop the models team, delegate ownership, give direct feedback, and grow team leads.
Run model launches end-to-end, including integrations, testing and evaluations, pricing, metering, capacity, security, documentation, and announcements.
Prepare day-zero model launches so they can ship promptly, with tested capabilities and accurate information.
Ensure catalog capabilities, limits, versions, and prices accurately reflect what developers receive; identify regressions and mismatches proactively.
Own evaluations, capability maps, per-task rankings, model recommendations, and auto-routing profiles as model intelligence comes online.
Connect evaluation regressions to routing decisions and ensure recommendations and rankings are grounded in trustworthy methodology.
Make product decisions about which models and routing profiles to offer and what market intelligence to publish, informed by usage, quality, reliability, and cost data.
Maintain a lightweight operating cadence that tracks ownership, progress, blockers, and upcoming launches while aligning stakeholders.
Manage provider expectations and keep Engineering, Product, Partnerships, and other stakeholders informed and aligned.
Automate recurring launch, evaluation, catalog, pricing, regression-detection, and provider-follow-up workflows to reduce manual effort as the catalog grows.
Deliver auto-routing that measurably improves cost or quality compared with a fixed model choice.
Define, measure, and monitor model and provider health; manage incidents and address root causes.

Benefits

Medical/Rx insurance
Dental insurance
Vision insurance
Flexible spending accounts
Commuter spending accounts
Fertility and family-forming benefits
On-demand mental health support and Employee Assistance Program
Global travel medical insurance
Short- and long-term disability insurance
Life and accident insurance
401(k) retirement savings plan
Employee stock participation plan
Flexible paid time off covering vacation and sick leave
Leave programs, including parental, pregnancy health, medical, and bereavement leave
Equity plan participation