AI Deployment Strategist

Join Fireworks as an AI Deployment Strategist, a hybrid technical/commercial role where you'll own the "why" and "what" of customer deployments. You'll partner with sales, manage the post-sale technical relationship, serve as a trusted advisor, and act as the technical escalation point for production issues. You'll also represent customer priorities in internal planning and own the technical narrative for business reviews. The ideal candidate has 4+ years in a technical, customer-facing role, direct experience with LLMs in production, and a strong technical foundation.

• Partner with Sales during late-stage deals and early post-sale to map the customer's technical and organizational landscape, quantify the business case for the deployment, and define a scoped pilot with clear milestones and exit criteria.
• Own the post-sale technical relationship from kickoff through go-live, including model deployment, integration architecture, SSO/security configuration, and performance benchmarking.
• 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, and driving usage against business objectives.
• 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
• 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
• Direct experience with LLMs in production — understanding of probabilistic model behavior, prompt engineering, fine-tuning, RAG, and/or agent architectures
• Bonus: experience with inference optimization, model serving infrastructure, or open-source model ecosystems (Llama, Mixtral, DeepSeek, etc.)
• Strong technical foundation: comfortable with APIs, cloud infrastructure (AWS/GCP/Azure), and enough hands-on coding ability to debug integrations, not just describe them
• 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
• Excellent written and verbal communication — able to translate between ML engineers and business stakeholders fluently
• Track record of managing enterprise relationships end-to-end: technical delivery, executive communication, and commercial outcomes (renewal/expansion)