AI Deployment Strategist

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 i [... source excerpt omitted ...] e 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 b [... source excerpt omitted ...] 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 e