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NEXTMOVEFDE careers · United States
Weights & Biases

AI Engineer- Gen AI/SWE- Weights & Biases

AI summary of the role

Senior applied AI engineer at Weights & Biases, building production-grade GenAI workflows and agentic systems at the research-to-product boundary.

What you’ll do

  • Ship end-to-end GenAI workflows (prompting → RAG → tools/agents → eval → serve) with reproducible repos, W&B Reports, and dashboards.
  • Build agentic systems (tool use, function calling, multi-step planners) with MCP servers/clients and secure tool/resource integrations.
  • Design evaluation harnesses (RAG/agent evals, golden sets, regression tests, telemetry) and drive continuous improvement via offline + online metrics.
  • Build in public: publish engineering artifacts (code, docs, talks, tutorials) and engage with OSS and customer engineers.

What you’ll bring

  • 6+ years building production systems; strong Python or TypeScript + system design, testing, CI/CD, observability.
  • Shipped LLM-powered features (tools/agents/function calling) with measurable impact (latency/cost/reliability).
  • Implemented planners/executors, tool orchestration, sandboxing, and failure taxonomies.
  • Pragmatic mastery of RAG: chunking, embeddings, vector/hybrid search, rerankers.

Technologies

Python · TypeScript · LLM · RAG · MCP · vector databases · CI/CD · agent frameworks · evaluation harnesses

Source and classification

Internal deployment & tooling · Evidence for this classification:

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. What You'll Do: The AI team is a hands-on applied AI group at Weights & Biases that turns frontier research into teachable workflows. We collaborate with leading enterprises and the OSS community. We are the team that took W&B from a few hundred users to millions of users and one of the most beloved tools in the ML community. A senior applied role at the
More from the job description

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. What You'll Do: The AI team is a hands-on applied AI group at Weights & Biases that turns frontier research into teachable workflows. We collaborate with leading enterprises and the OSS community. We are the team that took W&B from a few hundred users to millions of users and one of the most beloved tools in the ML community. A senior applied role at the research-to-product boundary. You will design, implement, and evaluate LLM applications and agents with cutting-edge techniques from the latest research, then document and teach them to our community and customers. The focus is application, not novel research: rapid prototyping, careful evaluation, and production-grade reference implementations with clear trade-offs. We prioritize responsible, safe deployment and reproducibility. About the role: Ship end-to-end GenAI workflows (prompting → RAG → tools/a [... source excerpt omitted ...] ents → eval → serve) with reproducible repos, W&B Reports, and dashboards others can run. Build agentic systems (tool use, function calling, multi-step planners) with MCP servers/clients and secure tool/resource integrations. Design evaluation harnesses (RAG/agent evals, golden sets, regression tests, telemetry) and drive continuous improvement via offline + online metrics. Build in public: Publish engineering artifacts (code, docs, talks, tutorials) and engage with OSS and customer engineers; turn repeated patterns into reusable templates. Partner with product/solutions to launch LLM-powered features with clear latency/cost/SLO targets and safety/guardrail checks. Run gro [... source excerpt omitted ...] eproducible artifacts. Preferred: Experience building with AI SDKs / agent frameworks (e.g., TypeScript/Python SDKs, planning libraries) and shipping developer-facing examples. Production agent security/sandboxing, red-teaming, and policy/PII enforcement. Operated eval platforms or built judge models/heuristics; experience leading metrics reviews with product/UX. Customer-facing enablement: templates or reference implementations adopted by external teams at scale. Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here ar

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