Manager, Field Engineering
Remote • San Mateo • FullTime
Posted 6h ago
Job Location
San Mateo
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Fireworks is seeking a Manager, Field Engineering to lead a team responsible for driving technical evaluations and production adoption of their AI inference and fine-tuning platform. This is a player-coach role where you will manage and develop a distributed team of hands-on engineers while remaining deeply technical yourself. You will act as a crucial link between the field and the rest of the company, coaching engineers, unblocking complex evaluations, and ensuring high technical standards for customer engagements across latency, throughput, cost, security, and scalability. You will collaborate with regional sales leadership to scale the engagement model, codify best practices, and build the team.
Responsibilities
- Lead, coach, and grow a distributed team of Field Engineers, including hiring, onboarding, and development.
- Own the team's engagement portfolio, allocating engineers and ensuring consistent execution from discovery to production.
- Lead complex evaluations end-to-end, stepping in on high-stakes or technically challenging deals.
- Coach Account Executives and Field Engineers in real-time to improve deal quality and outcomes.
- Build and refine the Field Engineering playbook, including discovery frameworks, POC templates, and reference architectures.
- Serve as the internal voice of the team and customers, influencing the product roadmap and translating pain points into improvements.
- Partner with revenue leadership on pipeline health, forecasting, and territory planning.
- Stay hands-on by building and shipping alongside engineers, including POCs, load testing, and model-serving configurations.
- Track and improve team operating metrics such as win rates, velocity, POC cycle time, and customer adoption.
Requirements
- 8+ years of overall experience, with at least 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, model serving, fine-tuning workflows (SFT; DPO/RFT a plus), and deploying models on GPU infrastructure (AWS, Azure, GCP).
- Demonstrated ability to build production software with customers and ship code in production environments.
- Proven track record of developing engineers through coaching and direct feedback.
- Ability to partner effectively with Sales while maintaining technical integrity and customer trust.
- Strong communication skills for discovery calls, executive presentations, and technical debugging.
- Builder mindset, thriving in fast-moving startup environments and creating structure.
- Willingness to travel up to 30% for customer engagements and team onsites.