Manager Field Engineering
Fireworks AI operates an AI platform for production inference and training of open-source models.
Maintainer signals as of 9/25/2026
Funding history
About Fireworks AI
Fireworks AI provides serverless and dedicated model inference, model deployment, and supervised and reinforcement fine-tuning for developers and enterprises building AI applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead and develop Field Engineers while remaining hands-on in customer engagements. You will allocate engineers across evaluations, guide discovery through production plans, coach technical and sales teams, improve field playbooks, and communicate customer insights internally. You will build and ship POCs, optimize performance, support model-serving and fine-tuning work, manage post-sales handoffs, and improve engagement metrics.
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
- Knowledge of LLM inference trade-offs, model serving, fine-tuning workflows, and GPU infrastructure
- Experience deploying models on AWS, Azure, and GCP
- Experience building production software with customers
- Experience coaching and developing engineers
- Ability to partner with Sales while maintaining technical integrity and customer trust
- Communication skills for discovery calls, executive presentations, and technical debugging
- Willingness to travel up to approximately 30%
Responsibilities
- Lead, coach, hire, onboard, and develop a distributed team of Field Engineers
- Own the engagement portfolio and allocate engineers across discovery, demos, POCs, and production integrations
- Lead complex evaluations from discovery through architecture, POC, and production planning
- Coach Account Executives and Field Engineers to improve deal quality and outcomes
- Build and refine discovery frameworks, POC templates, reference architectures, and field artifacts
- Systematize field insights and customer pain points to influence platform improvements
- Partner on pipeline health, forecasting, and territory planning
- Build and ship POCs and MVPs, perform load testing, develop evaluation and fine-tuning pipelines, and guide model-serving choices
- Ensure strong post-sales handoffs for onboarding and adoption
- Track and improve win rates, velocity, POC cycle time, utilization, and customer adoption outcomes
Benefits
- Equity