Manager, Field Engineering
San Mateo · New York · 2+ years experience · Full-time · Hybrid · Posted Sep 29, 2026
At a glance
- Experience
- 2+ years experience
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- San Mateo · New York
About Fireworks AI
- Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
- We're hiring a Manager, Field Engineering to lead a team of Field Engineers driving technical evaluations and production adoption of Fireworks' inference and fine-tuning platform. This is a player-coach role — you'll manage and grow a distributed team of hands-on engineers while staying deeply technical yourself, leading engagements end-to-end at some of the most ambitious AI-native companies and enterprises.
- As Manager you will be a critical link between the field and the rest of the company: coaching your field engineers in real time, unblocking complex evaluations, and ensuring every customer engagement meets a high technical bar across latency, throughput, cost, security, and scalability. You'll work closely with regional sales leadership to scale the engagement model, codify the playbook, and build the team.
- This is a hands-on leadership role. Your credibility with field engineers comes from having built production AI systems with customers, not just having managed people who did. You will still get in the weeds when the stakes are highest with shipping POCs, performance optimizations, co—lead training engagements with our research team and debugging alongside your team.
About the role
- The Manager, Field Engineering will lead and grow a distributed team of hands-on engineers driving technical evaluations and production adoption of Fireworks' inference and fine-tuning platform.
- This is a player-coach role that requires managing a team while remaining deeply technical to lead high-stakes engagements and build production AI systems with customers.
Responsibilities
- Lead, coach, and grow a distributed team of Field Engineers.
- Own the team's engagement portfolio, including discovery, demos, POCs, and production integrations.
- Lead complex evaluations end-to-end, personally stepping in on high-stakes or technically challenging deals.
- Coach AEs and Field Engineers in real time to improve deal quality and outcomes.
- Build and refine the Field Engineering playbook, including discovery frameworks and reference architectures.
- Systematize field insights to influence the product and engineering roadmap.
- Partner with revenue leadership on pipeline health, forecast calls, and territory planning.
- Build and ship POCs, MVPs, and performance optimizations alongside engineers.
- Track and improve team operating metrics such as win rates, cycle time, and utilization.
Requirements
- 8+ years of overall experience, including 2+ years managing Field Engineering, Solutions Engineering, Forward Deployed Engineering, or Pre-Sales teams.
- Hands-on experience in enterprise software or AI infrastructure.
- Strong technical foundation and fluency in the LLM stack, including inference trade-offs and model serving.
- Experience with fine-tuning workflows and deploying models on GPU infrastructure across AWS, Azure, and GCP.
- Demonstrated ability to build production software with customers.
- Track record of developing engineers through coaching and direct feedback.
- Proven ability to partner effectively with Sales while maintaining technical integrity.
- Strong communication skills for both technical debugging and executive-level presentations.
- Willingness to travel up to approximately 30%.
Preferred qualifications
- Experience with DPO (Direct Preference Optimization) or RFT (Reinforcement Fine-Tuning)
Workplace
- Role is based in San Mateo or New York.
- Requires travel up to approximately 30% for customer engagements and team onsites.
Skills
- LLM Stack
- vLLM
- SGLang
- TensorRT-LLM
- AWS
- Azure
- GCP
- SFT
- DPO
- RFT
- GPU Infrastructure
- Model Serving
