Engineering Manager, Provider Ecosystem

ABOUT the company

The company is the leading AI routing and infrastructure layer that enterprises use to access, manage, and optimize the best large language models across providers—without lock-in, capacity constraints, or unnecessary cost. We power the most advanced AI teams in the world by giving them the flexibility to move fast, scale confidently, and stay future-proof as models evolve.

As enterprise adoption of AI accelerates, the company sits at the center of how organizations operationalize LLMs across research, product, and production workloads.

ABOUT THE ROLE

The Provider Ecosystem team owns the supply side of the company: every model, endpoint, and provider the router can send a request to. That means hundreds of providers, thousands of endpoints, and millions of requests a day, in a model landscape that changes every week.

You’ll be at the front of the industry. Labs and inference providers want to reach the company’s users, so this team gets early access to novel inference offerings, often through exclusive and stealth launches, and gets them live on day zero.

This is a hands-on leadership role reporting to the VPE. You’ll grow the team, stay deep in the code, and be the company’s technical face to the labs and providers we partner with.

WHAT YOU'LL DO

• Lead the team: hire and grow strong engineers, set the roadmap, stay hands-on in code reviews and incidents, and advocate for the team with leadership.

• Core Provider: own provider adapters, the endpoint lifecycle, and routing. Be the technical counterpart for top providers, run day-zero and stealth launches, and work with GTM, BD, and legal to get providers from signed NDA to live in weeks, not months.

• Multi-Modal: lead the expansion beyond text into image, video, audio, and embeddings, plus realtime and batch inference.

• Benchmarks: own evals and inference quality, and turn that data into routing decisions and direct feedback that makes providers better.

WHAT WE'RE LOOKING FOR

• 4+ years of engineering management experience, including at least one environment where you built or scaled a team during a period of rapid growth.

• Strong technical foundation in distributed systems, API design, and LLM inference. You understand how inference is served (streaming, tool calling, prompt caching, quantization, throughput and latency trade-offs), how provider APIs differ from each other, and what it takes to route millions of requests across hundreds of heterogeneous endpoints.

• Hands-on and comfortable staying that way. You write code, use AI-assisted development tools, and lead by example in a team where everyone ships.

• Comfortable being externally facing. You can sit across from a model lab’s engineering team, negotiate an integration, and represent the company’s technical requirements without a PM in the room.

• Data-driven about quality. You want benchmarks, evals, and production telemetry deciding which provider gets traffic, not vibes.

• Proven ability to recruit and retain strong engineers. Ideally, you’ve built teams people want to join and you bring a network of talent with you.

• High agency and clear communication. You don’t wait for direction, you identify what matters, make a plan, and drive it forward. You speak up when you disagree and back it with substance.

• Pragmatic about what a lean engineering org actually needs versus what a 500-person org would do. You optimize for speed and clarity, not process.

NICE TO HAVES

• Experience at an inference provider, model lab, or GPU cloud, or building products on top of many LLM APIs at once.

• Experience with our stack: TypeScript, Cloudflare Workers, Postgres, ClickHouse, GCP, or Vercel.

• Background in evals, benchmarking, or routing and load-balancing systems.

• Experience shipping multimodal APIs (image, video, speech, embeddings) or realtime and batch inference.

• Experience running vendor security and compliance reviews (NDA, DPA, SOC 2) as part of a partner onboarding process.

• Existing user of the company, or active side projects in AI infrastructure or developer tooling.

If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone who is excited to join the team.