Engineering Manager, Forward Deployed Engineering (LLM)

Baseten powers mission-critical inference for AI companies like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. They recently raised a $1.5B Series F led by Altimeter Capital, Conviction Partners, and Spark Capital.

As an Engineering Manager (Player & Coach), you will lead and mentor a team of Forward Deployed Engineers focused on building, scaling, and optimizing LLM inference workloads for Baseten customers. You will guide your team through designing, deploying, and managing high-performance, low-latency AI applications on Baseten's platform. FDE at Baseten is not a sales function; it's a mix of engineering, product, and customer architects who contribute to the core codebase and drive the feature roadmap.

• Lead, mentor, and grow a team of Forward Deployed Engineers, providing guidance on technical direction, project execution, and professional development.
• Set clear goals and ensure timely, high-quality delivery across customer-facing projects involving LLM deployment and inference optimization.
• Collaborate with leadership to align team priorities with company and customer goals.
• Act as a player-coach, driving strategic product initiatives and customer engagements while leading the team.
• Develop and maintain software systems using general-purpose programming languages, with a preference for Python.
• Drive customer impact by designing, implementing, and deploying Baseten solutions end-to-end, from problem framing to production deployment and monitoring.
• Deliver with velocity, turning vague objectives into clear specs and well-defined PoCs.
• Optimize and enhance AI/ML projects, contributing to the continuous improvement of the technical stack.
• Own products and customer projects end-to-end, functioning as both engineer, project manager, and product manager.

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or related field.
• 4+ years of professional software engineering experience, including 1+ year in a leadership or mentorship capacity.
• Strong programming skills in Python, with production experience in building or optimizing ML inference systems.
• Proven experience with LLMs, inference optimization, or serving frameworks (e.g., vLLM, TensorRT, Triton, Hugging Face, Ray Serve).
• Familiarity with observability, profiling, and cost/performance tradeoffs in production ML systems.
• Excellent communication and collaboration skills.

• Experience leading customer-facing engineering teams or working directly with enterprise partners.
• Deep understanding of GPU infrastructure, distributed inference, or model compression techniques.

• Competitive compensation, including meaningful equity.
• 100% coverage of medical, dental, and vision insurance for employee and dependents.
• Flexible PTO policy including company-wide Winter Break.
• Paid parental leave.
• Fertility and family-building stipend through Carrot.
• Company-facilitated 401(k).
• Exposure to a variety of ML startups.