Job description

ABOUT US: 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. ABOUT THE ROLE Fireworks AI is looking for an AI Deployment Strategist to be the technical backbone of our relationship with customers building on our fast inference platform. You'll be the connective tissue between customer engineering teams and Fireworks' product, engineering, and applied AI teams — driving successful onboarding, deep technical adoption, and long-term account health for companies running production AI workloads at scale. This is a hybrid technical/commercial role. You'll need enough depth to debug a customer's inference pipeline, discuss quantization tradeoffs, or advise on model routing and fine-tuning strategy — and enough business judgment to run a QBR, spot expansion opportunity, and manage renewal risk before it becomes a problem. Think of it as "product manager for the customer's problem": you own the why and the what — scoping the business case, defining success criteria, and managing the relationship end-to-end. You're embedded with your accounts from early technical evaluation through production and beyond. WHAT YOU'LL DO Deployment Strategy & Value Scoping - Partner with Sales during late-stage deals and early post-sale to map the customer's technical and organizational landscape — who the real stakeholders are, what "success" looks like, and where the risk sits - Quantify the business case for the deployment (cost-to-serve, latency/quality targets, ROI vs. the customer's current approach) and define a scoped pilot with clear milestones and exit criteria - Author the internal scoping brief that AI Field Engineering builds against — you own the "why" and "what," they own the "how" Onboarding & Technical Deployment - Own the post-sale technical relationship from kickoff through go-live, including model deployment, integration architecture, SSO/security configuration, and performance benchmarking - Partner with AI Field Engineering to deliver the successful transition from PoC to production - Build and execute joint success plans with clear milestones, ownership, and timelines Trusted Advisor & Adoption - Serve as the primary technical point of contact for a portfolio of strategic accounts, building deep relationships with engineering leaders, ML/platform teams, and power users - Advise customers on model selection, fine-tuning, prompt engineering, latency/cost optimization, and agent architecture as their usage matures - Drive usage against business objectives — not just technical enablement, but measurable outcomes (latency SLAs, cost per token, model quality, uptime) Troubleshooting & Escalation Management - Act as the technical escalation point for production issues, coordinating with Engineering and Support to drive resolution - Maintain runbooks and playbooks that reduce time-to-resolution across the account portfolio Voice of the Customer - Synthesize patterns across your accounts and feed them into product and engineering roadmaps - Represent customer priorities in internal planning, particularly around model support, tooling gaps, and platform reliability - Track a tight feedback loop between what customers are building and what Fireworks ships next Expansion, Renewal & Business Reviews - Own the technical narrative for quarterly/executive business reviews (QBRs/EBRs), including adoption trends, ROI, and roadmap alignment - Partner with the Account Executive on renewal strategy and identify expansion opportunities tied to new use cases, teams, or workloads - Forecast and proactively flag account health risks before they threaten retention WHAT WE'RE LOOKING FOR - Bachelor's degree required - 4+ years in a technical, customer-facing role: Deployment Strategy, Technical Account Management, Solutions Engineering, Forward-Deployed Engineering, or Technical Customer Success at an enterprise software or AI/ML company - Strong technical foundation: comfortable with APIs, cloud infrastructure (AWS/GCP/Azure), and enough hands-on coding ability to debug integrations, not just describe them - Direct experience with LLMs in production — understanding of probabilistic model behavior, prompt engineering, fine-tuning, RAG, and/or agent architectures - Track record of managing enterprise relationships end-to-end: technical delivery, executive communication, and commercial outcomes (renewal/expansion) - Excellent written and verbal communication — able to translate between ML engineers and business stakeholders fluently - Comfortable owning ambiguity in a fast-moving, early-stage function; you'll be shaping the playbook for this role at Fireworks, not just following one - Experience scoping high-value engagements — value-based/TCO-ROI framing, defining pilot success criteria, writing scoping docs or PRDs — gained in a Deployment Strategist, Forward-Deployed Engineer, or similar "product manager for the field" capacity is a strong plus - Bonus: experience with inference optimization, model serving infrastructure, or open-source model ecosystems (Llama, Mixtral, DeepSeek, etc.) WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

Requirements

Must-haves

Deployment Strategy & Value Scoping
Partner with Sales during late-stage deals and early post-sale to map the customer's technical and organizational landscape — who the real stakeholders are, what "success" looks like, and where the risk sits
Quantify the business case for the deployment (cost-to-serve, latency/quality targets, ROI vs. the customer's current approach) and define a scoped pilot with clear milestones and exit criteria
Author the internal scoping brief that AI Field Engineering builds against — you own the "why" and "what," they own the "how"
Onboarding & Technical Deployment
Own the post-sale technical relationship from kickoff through go-live, including model deployment, integration architecture, SSO/security configuration, and performance benchmarking
Partner with AI Field Engineering to deliver the successful transition from PoC to production
Build and execute joint success plans with clear milestones, ownership, and timelines
Trusted Advisor & Adoption
Serve as the primary technical point of contact for a portfolio of strategic accounts, building deep relationships with engineering leaders, ML/platform teams, and power users
Advise customers on model selection, fine-tuning, prompt engineering, latency/cost optimization, and agent architecture as their usage matures
Drive usage against business objectives — not just technical enablement, but measurable outcomes (latency SLAs, cost per token, model quality, uptime)
Troubleshooting & Escalation Management
Act as the technical escalation point for production issues, coordinating with Engineering and Support to drive resolution
Maintain runbooks and playbooks that reduce time-to-resolution across the account portfolio
Voice of the Customer
Synthesize patterns across your accounts and feed them into product and engineering roadmaps
Represent customer priorities in internal planning, particularly around model support, tooling gaps, and platform reliability
Track a tight feedback loop between what customers are building and what Fireworks ships next
Expansion, Renewal & Business Reviews
Own the technical narrative for quarterly/executive business reviews (QBRs/EBRs), including adoption trends, ROI, and roadmap alignment
Partner with the Account Executive on renewal strategy and identify expansion opportunities tied to new use cases, teams, or workloads
Forecast and proactively flag account health risks before they threaten retention

Nice-to-haves

Bonus: experience with inference optimization, model serving infrastructure, or open-source model ecosystems (Llama, Mixtral, DeepSeek, etc.)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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