Technical Account Manager, EnterpriseActive$140K–$210K

Fireworks AI
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The opportunity

Fireworks AI is looking for a Technical Account Manager (TAM) 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…

What you'll do

  • Own the post-sale technical relationship from kickoff through go-live,: including model 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

  • 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 enablement, but measurable outcomes (latency SLAs, cost per token, model quality, uptime)

What they're looking for

  • + years in a technical, customer-facing role: Technical Account Management, Solutions Engineering, Forward-Deployed Engineering, or Technical Customer Success at an enterprise software or AI/ML company
  • Strong technical foundation: comfortable with APIs, cloud infrastructure (AWS/GCP/Azure), and enough hands-on coding ability to debug integrations, not just describe them
  • Direct experience with LLMs in production: understanding of probabilistic model behavior, prompt engineering, fine-tuning, RAG, and/or agent architectures
  • Track record of managing enterprise relationships end-to-end: technical delivery, executive communication, and commercial outcomes (renewal/expansion)
  • Excellent written and verbal communication: able to translate between ML engineers and business stakeholders fluently
  • Comfortable owning ambiguity in a fast-moving, early-stage function; you'll: be shaping the TAM playbook, not just following one
  • Bonus: experience with inference optimization, model serving infrastructure,: or open-source model ecosystems (Llama, Mixtral, DeepSeek, etc.)