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Fireworks is a Series D AI infrastructure company (valued at $17.5B, backed by NVIDIA, Sequoia, AMD, and others) building a platform for specialized intelligence. The company enables enterprises to build, train, and serve AI models tailored to their data and workflows, powering production AI workloads at scale across text, image, embedding, audio, and multimodal domains.
As Technical Account Manager for Enterprise, you'll be the technical backbone of relationships with strategic customers building on Fireworks' fast inference platform. This hybrid technical/commercial role bridges customer engineering teams with Fireworks' product, engineering, and applied AI teams.
Key responsibilities include:
**Onboarding & Deployment**: Own post-sale technical relationships from kickoff through production go-live. Manage model deployment, integration architecture, SSO/security configuration, and performance benchmarking. Partner with AI Field Engineering to transition customers from PoC to production, building joint success plans with clear milestones.
**Technical Advisory**: Serve as primary technical contact for a portfolio of strategic accounts. Advise on model selection, fine-tuning, prompt engineering, latency/cost optimization, and agent architecture. Drive measurable outcomes tied to business objectives (latency SLAs, cost per token, model quality, uptime).
**Troubleshooting & Escalation**: Act as technical escalation point for production issues, coordinating with Engineering and Support. Maintain runbooks and playbooks to reduce resolution time across accounts.
**Voice of Customer**: Synthesize patterns across accounts and feed into product/engineering roadmaps. Represent customer priorities in internal planning around model support, tooling, and platform reliability.
**Expansion & Renewal**: Own technical narrative for QBRs/EBRs, including adoption trends and ROI. Partner with Account Executives on renewal strategy and identify expansion opportunities. Proactively flag account health risks.
Required: 4+ years in technical customer-facing roles (TAM, Solutions Engineering, Forward-Deployed Engineering, or Technical Customer Success) at enterprise software or AI/ML companies. Strong technical foundation with APIs, cloud infrastructure (AWS/GCP/Azure), and hands-on coding ability. Direct production LLM experience including probabilistic model behavior, prompt engineering, fine-tuning, RAG, and agent architectures. Track record managing enterprise relationships end-to-end. Excellent written and verbal communication. Comfortable with ambiguity in early-stage functions.
Bonus: inference optimization, model serving infrastructure, or open-source model ecosystem experience (Llama, Mixtral, DeepSeek).
