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Fireworks AI

AI inference platform for model deployment

Manager, Field Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-time$270k - $310k /yr

About the Job

Requirements

  • You have 8+ years of overall experience, including 2+ years managing Field Engineering, Solutions Engineering, Forward Deployed Engineering, or Pre-Sales teams, with hands-on experience in enterprise software or AI infrastructure.
  • You have a strong technical foundation and fluency in the large language model stack: inference trade-offs, model serving, fine-tuning workflows (supervised fine-tuning; direct preference optimization and reinforcement fine-tuning are a plus), and deploying models on GPU infrastructure across Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
  • You have demonstrated the ability to build production software with customers, including shipping code running in someone else's production environment and being able to do it when a deal demands it.
  • You have a track record of developing engineers through coaching, direct feedback, and growing individual contributors into senior and lead roles.
  • You have proven ability to partner effectively with Sales while maintaining technical integrity and customer trust in high-stakes deal environments.
  • You have strong communication skills to run a discovery call, present to a vice president or chief technology officer, and debug a latency issue with a machine learning engineer.
  • You thrive in fast-moving startup environments and enjoy creating structure where little exists.
  • You are willing to travel up to approximately 30% for customer engagements and team onsites.
  • You can architect solutions and teach engineers why they are appropriate.
  • You can run a portfolio of concurrent engagements and maintain consistent execution across the team.
  • You have deep familiarity with the AI inference, fine-tuning, and production generative AI market and ecosystem.
  • You have a sophisticated understanding of enterprise cloud platforms and complex integration environments, and can translate technical architecture into business value.
  • You have strong written and verbal communication skills for internal documentation, executive-ready summaries, and customer-facing technical artifacts.
  • You have commercial instincts to size opportunities, understand deal dynamics, and align team effort to revenue acceleration.
  • You are comfortable with ambiguity and can create processes where none exist without slowing the team down.

Responsibilities

  • Lead, coach, and grow a distributed team of Field Engineers by hiring, onboarding, developing, and holding the team to a high bar for technical excellence and customer outcomes.
  • Own the team's engagement portfolio by allocating engineers to pursuits and ensuring consistent execution across discovery, demos, proofs of concept, and production integrations.
  • Lead complex evaluations end to end, from discovery through architecture and proof of concept to production planning, personally stepping in on the highest-stakes or most technically challenging deals.
  • Coach account executives and Field Engineers in real time to improve deal quality and close outcomes by reviewing architectures, sitting in on calls, and running post-mortems on wins and losses.
  • Build and refine the Field Engineering playbook, including discovery frameworks, proof-of-concept templates, reference architectures, and reusable field artifacts.
  • Represent the team and customers internally by systematizing field insights, influencing the product and engineering roadmap, and translating recurring pain points into platform improvements.
  • Partner with revenue leadership on pipeline health, forecast calls, and regional territory planning.
  • Build and ship alongside engineers when needed, including proofs of concept and minimum viable products, load testing, evaluation and fine-tuning pipelines, and model-serving choices across vLLM, SGLang, and TensorRT-LLM; ensure strong post-sales handoffs for onboarding and adoption.
  • Track and improve team operating metrics, including win rates and velocity, proof-of-concept cycle time, utilization, and customer adoption outcomes.

Desired Qualifications

  • Direct preference optimization and reinforcement fine-tuning experience is a plus.

About the Company

Fireworks AI

AI inference platform for model deployment

Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.

Company size
201-500
Company stage
Series D
Total funding
$1.8B
Headquarters
Redwood City, CA
Founded
2022

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