Technical Account Manager, Enterprise

Fireworks AI Fireworks AI · Data AI · London, United Kingdom +2 · Go To Market

Technical Account Manager for an enterprise AI inference platform, focusing on customer onboarding, technical adoption, troubleshooting, and acting as a liaison between customers and internal teams. Requires strong technical understanding of LLMs in production, including inference, fine-tuning, RAG, and agent architectures, as well as customer relationship management and commercial acumen.

What you'd actually do

  1. Own the post-sale technical relationship from kickoff through go-live, including model deployment, integration architecture, SSO/security configuration, and performance benchmarking
  2. 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
  3. Act as the technical escalation point for production issues, coordinating with Engineering and Support to drive resolution
  4. Synthesize patterns across your accounts and feed them into product and engineering roadmaps
  5. Own the technical narrative for quarterly/executive business reviews (QBRs/EBRs), including adoption trends, ROI, and roadmap alignment

Skills

Required

  • 4+ years in a technical, customer-facing role
  • Strong technical foundation: comfortable with APIs, cloud infrastructure (AWS/GCP/Azure)
  • Direct experience with LLMs in production
  • Track record of managing enterprise relationships end-to-end
  • Excellent written and verbal communication

Nice to have

  • enough hands-on coding ability to debug integrations
  • experience with inference optimization
  • model serving infrastructure
  • open-source model ecosystems (Llama, Mixtral, DeepSeek, etc.)

What the JD emphasized

  • production AI workloads at scale
  • debug a customer's inference pipeline
  • advise on model routing and fine-tuning strategy
  • enough hands-on coding ability to debug integrations
  • Direct experience with LLMs in production
  • Track record of managing enterprise relationships end-to-end
  • shaping the TAM playbook

Other signals

  • customer-facing technical role
  • production AI workloads
  • inference platform
  • customer adoption
  • technical troubleshooting
  • voice of the customer