About this role
Fireworks is seeking an AI Deployment Strategist to own the technical customer relationship for companies building production AI workloads on its inference platform. The role combines deployment strategy, technical advising and commercial account management, from early evaluation through production and ongoing adoption.
Responsibilities
- Partner with Sales to identify customer stakeholders, risks and success criteria. Quantify deployment value using cost-to-serve, latency, quality and ROI; scope pilots with milestones and exit criteria, and write briefs for AI Field Engineering.
- Lead the post-sale relationship from kickoff to go-live, covering model deployment, integration architecture, SSO and security configuration, and performance benchmarking. Work with AI Field Engineering to move proofs of concept into production and maintain joint success plans.
- Advise strategic accounts on model selection, fine-tuning, prompt engineering, agent architecture, and latency and cost optimization. Track outcomes including latency SLAs, cost per token, model quality and uptime.
- Coordinate production-issue escalations with Engineering and Support, maintain resolution runbooks, and bring customer feedback on model support, tooling and reliability into product planning.
- Present adoption, ROI and roadmap alignment in quarterly and executive business reviews; work with the Account Executive on renewals, expansion opportunities and account-health risks.
Requirements
- Bachelor's degree and 4+ years in a technical, customer-facing role such as deployment strategy, technical account management, solutions engineering, forward-deployed engineering or technical customer success at an enterprise software or AI/ML company.
- Ability to work with APIs, AWS, GCP or Azure, and code sufficiently to debug integrations. Direct experience with production LLMs and understanding of probabilistic model behavior, prompt engineering, fine-tuning, RAG and/or agent architectures.
- Experience managing enterprise relationships across technical delivery, executive communication and renewal or expansion outcomes; strong written and verbal communication and comfort shaping processes in an ambiguous, fast-moving function.
Preferred
Experience scoping high-value engagements through TCO/ROI analysis, pilot criteria and scoping documents or PRDs. Inference optimization, model serving infrastructure and open-source model ecosystems such as Llama, Mixtral or DeepSeek are bonuses.
The position is full-time and hybrid, listed in San Mateo or New York. Annual base pay is $165K–$220K, with equity offered; base pay may vary by market location, skills and experience.