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Manager, Field Engineering

Lead a distributed team of Field Engineers to drive technical evaluations and production adoption of Fireworks' AI platform.

Location
San Mateo
Compensation
Not disclosed
Level
lead
Type
full time

Posted by employer 3 days ago

First seen on Joblaze 2 days ago

Last verified on the company career page 4 hours ago

Skills & Technologies

What you'll build

  • Lead and grow a team of Field Engineers
  • Own team's engagement portfolio
  • Lead complex evaluations end-to-end
  • Build and refine the Field Engineering playbook
  • Track and improve team's operating metrics

Must have

  • 8+ years of overall experience
  • 2+ years managing Field Engineering or similar teams
  • Strong technical foundation in LLM stack
  • Demonstrated ability to build production software
  • Proven ability to partner effectively with Sales

Practical constraints

  • Willingness to travel (up to ~30%)

Role intensity

30% coding — mostly leadership/strategy

AI in the day-to-day

Fireworks powers production AI with hundreds of state-of-the-art open models across various workloads.

Requirements

Experience
8+ years

Not disclosed in this posting: compensation, work arrangement, visa sponsorship.

Joblaze summary

The Manager of Field Engineering at Fireworks AI leads a team of engineers focused on driving technical evaluations and production adoption of the company's AI platform. This role requires a strong technical background in AI infrastructure, particularly with LLMs, and the ability to manage complex customer engagements while maintaining high standards of execution. Ideal candidates have extensive experience in field engineering or similar roles, along with a proven track record of developing talent and collaborating effectively with sales teams. Fireworks AI fosters a collaborative environment, emphasizing hands-on leadership and continuous improvement.

Joblaze insights

  • Listed 2 days ago — first seen on Joblaze September 30, 2026. Last confirmed on Fireworks AI's careers page October 2, 2026.
  • AI/ML appears in 26.9% of 531 comparable lead management roles in United States; Azure appears in 2.8% of 531 comparable lead management roles in United States.

Quick facts

How much experience is required?
At least 8 years of relevant experience for this Manager, Field Engineering role.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, AWS, Azure, GCP.
What seniority level is this role?
Fireworks AI targets lead candidates for this position.
Is this full-time or contract?
Full-time for this Manager, Field Engineering role at Fireworks AI.

From the original posting

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.

What You'll Do

  • Lead, coach, and grow a distributed team of Field Engineers — hiring, onboarding, developing, and holding a high bar for technical excellence and customer outcomes

  • Own your team's engagement portfolio: allocate the right engineers to the right pursuits and ensure consistent execution across discovery, demos, POCs, and production integrations

  • Lead complex evaluations end-to-end (discovery → architecture → POC → production plan), personally stepping in on the highest-stakes or most technically challenging deals

  • Coach AEs and Field Engineers in real time to improve deal quality and close outcomes — reviewing architectures, sitting in on calls, and running sharp post-mortems on wins and losses

  • Build and refine the Field Engineering playbook: discovery frameworks, POC templates, reference architectures, and reusable field artifacts

  • Serve as the voice of your team and customers internally — systematizing field insights, influencing the product/engineering roadmap, and translating recurring pain points into concrete platform improvements

  • Partner with revenue leadership on pipeline health, forecast calls, and territory planning for your region

  • Stay hands-on when it matters: build/ship alongside your engineers (POCs/MVPs, load testing, eval + fine-tuning pipelines, model-serving choices across vLLM/SGLang/TensorRT-LLM) and ensure strong post-sales handoffs for onboarding and adoption

  • Track and improve your team's operating metrics — win rates and velocity, POC cycle time, utilization, and customer adoption outcomes

You May Be a Fit If

  • 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 LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT; DPO/RFT a plus), and deploying models on GPU infrastructure across AWS, Azure, and GCP

  • You have demonstrated ability to build production software with customers, not just advise on it — you have shipped code running in someone else's production environment and can still do it when a deal demands it

  • You have a track record of developing engineers — coaching, giving direct feedback, and growing individual contributors into senior and lead roles

  • You have proven your ability to partner effectively with Sales while maintaining technical integrity and customer trust in high-stakes deal environments

  • You have strong communication skills — able to run a sharp discovery call, present to a VP or CTO, and debug a latency issue with an ML engineer in the same afternoon

  • You have a builder mindset: you thrive in fast-moving, startup environments and enjoy creating structure where little exists

  • Willingness to travel (up to ~30%) for customer engagements and team onsites

You Excel In These Key Competencies

  • Technical depth with coaching instinct: able to both architect the solution and teach the engineer next to you why it's right

  • Operational rigor: able to run a portfolio of concurrent engagements and hit consistent execution across the team

  • Deep familiarity with the AI inference, fine-tuning, and production GenAI market and ecosystem

  • Sophisticated understanding of enterprise cloud platforms and complex integration environments, with the ability to translate technical architecture into business value

  • Strong written and verbal communication — internal docs, exec-ready summaries, and customer-facing technical artifacts that are sharp and clear

  • Commercial instincts: able to size opportunities, understand deal dynamics, and align your team's effort to revenue acceleration

  • Comfort with ambiguity: creates process where none exists without slowing the team down

Our Mission & Culture

Our mission is to make AI inference fast, affordable, and production-ready for every developer and enterprise. Our organization is flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

We are building a Field Engineering organization in that same image — engineers who lead with credibility earned in the codebase and the customer's infrastructure, who compress the feedback loop from field to roadmap, and who treat every customer deployment as a chance to make the platform better for everyone.

Why Fireworks?

  • Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.

Standard company text repeated across Fireworks AI's postings is omitted here.

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