AI Deployment Strategist

Fireworks • San Mateo, CA

20h

About The Position

Fireworks AI is seeking an AI Deployment Strategist to serve as the technical backbone of its customer relationships for organizations building on its fast inference platform. The role connects customer engineering teams with Fireworks’ product, engineering, and applied AI teams, leading onboarding, technical adoption, and long-term account health for customers running production AI workloads at scale.

This is a hybrid technical and commercial position. The strategist is expected to troubleshoot inference pipelines and advise on topics such as quantization, model routing, and fine-tuning, while also managing business reviews, identifying expansion opportunities, and addressing renewal risks. The role owns the customer problem’s purpose and scope: building the business case, defining success criteria, and managing the relationship from technical evaluation through production and ongoing account growth.

The position covers deployment strategy and value scoping, post-sale onboarding and technical deployment, customer advising and adoption, production troubleshooting and escalation management, customer feedback for product planning, and technical support for renewals, expansions, and executive business reviews. The strategist works closely with Sales, AI Field Engineering, Engineering, Support, and customer stakeholders.

Requirements

• Bachelor’s degree required.
• At least 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.
• Strong technical foundation, including comfort with APIs and cloud infrastructure such as AWS, GCP, or Azure.
• Hands-on coding ability sufficient to debug integrations.
• Direct experience with LLMs in production and understanding of probabilistic model behavior, prompt engineering, fine-tuning, RAG, and/or agent architectures.
• Track record managing enterprise relationships end-to-end, including technical delivery, executive communication, and commercial outcomes such as renewals or expansions.
• Excellent written and verbal communication skills, including the ability to translate between ML engineers and business stakeholders.
• Ability to own ambiguity in a fast-moving, early-stage function and help shape the role’s playbook.
• Comfort with scoping high-value engagements, value-based or TCO/ROI framing, defining pilot success criteria, and writing scoping documents or PRDs.

Nice To Haves

• Experience scoping high-value engagements in a Deployment Strategist, Forward-Deployed Engineer, or similar field-based product-management capacity.
• Experience with inference optimization, model-serving infrastructure, or open-source model ecosystems such as Llama, Mixtral, or DeepSeek.

Responsibilities

• Partner with Sales during late-stage deals and early post-sale to map customer technical and organizational landscapes, stakeholders, success criteria, and risks.
• Quantify deployment business cases, including cost-to-serve, latency and quality targets, and ROI versus the customer’s current approach.
• Define scoped pilots with clear milestones and exit criteria.
• Author internal scoping briefs for AI Field Engineering, owning the rationale and scope of engagements.
• Own the post-sale technical relationship from kickoff through go-live, including model deployment, integration architecture, SSO and security configuration, and performance benchmarking.
• Partner with AI Field Engineering to transition customers successfully from proof of concept to production.
• Build and execute joint success plans with clear milestones, ownership, and timelines.
• Serve as the primary technical point of contact for strategic accounts and build relationships with engineering leaders, ML and platform teams, and power users.
• Advise customers on model selection, fine-tuning, prompt engineering, latency and cost optimization, and agent architecture.
• Drive usage toward business objectives and measurable outcomes such as latency SLAs, cost per token, model quality, and uptime.
• Act as the technical escalation point for production issues and coordinate with Engineering and Support to resolve them.
• Maintain runbooks and playbooks to reduce time to resolution across the account portfolio.
• Synthesize customer patterns and feed them into product and engineering roadmaps.
• Represent customer priorities in internal planning, particularly for model support, tooling gaps, and platform reliability.
• Track feedback between customer needs and Fireworks’ product development.
• Own the technical narrative for quarterly and executive business reviews, including adoption trends, ROI, and roadmap alignment.
• Partner with Account Executives on renewal strategy and identify expansion opportunities tied to new use cases, teams, or workloads.
• Forecast account health and proactively flag risks to retention.

Benefits

• Opportunity to work on challenging AI infrastructure problems, including low-latency inference and scalable model serving.
• Opportunity to work with cutting-edge technology with global impact.
• Ownership and direct impact at a fast-growing team, with an emphasis on results and limited bureaucracy.
• Opportunity to collaborate with engineers and AI researchers.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level