Jobs Companies talentpluto Forward Deployed Engineer

Sobre este puesto de Forward Deployed Engineer en talentpluto

talentpluto · Presencial · San Francisco, California, United States

Location: San Francisco, CA

Work Model: Onsite, 5 days per week. Relocation support provided.

Industry: AI infrastructure / model inference

Compensation: $180,000 – $240,000 base, plus equity

About the Company

Our partner is a venture-backed AI infrastructure company delivering the fastest inference available on open models, serving both enterprise and serverless customers. They run their own compute, and customer demand currently outpaces the capacity they can bring online. The team is small, flat, and deliberately staying that way as they scale.

The Opportunity

This is a forward-deployed engineering role that owns the customer, not just the code. Sales takes the first meeting. From there you are both the customer's engineer and their point of contact: you decide what to prove, you build it, you keep it running in production, and you carry the relationship.

Because you sit closer to real production load than anyone else on the team, what you learn goes straight into the roadmap. You will report directly into engineering leadership, and the longer-term plan is for engineers in this function to own their own pods as the team grows. These are among the first hires into the function, so its shape is still yours to influence.

Responsibilities

  • Own assigned customer accounts end to end once the first sales meeting is complete
  • Win the technical evaluation by proving performance on the customer's own workload rather than a synthetic benchmark, and explain the result to their engineering team
  • Stand up dedicated deployments and optimize the full stack for each customer's workload
  • Own production for your accounts: investigate latency and error-rate regressions, resolve or route them, and communicate directly with the customer
  • Carry on-call responsibility for customer issues on your accounts
  • Feed real-world performance findings back to the engineering team to shape the product roadmap

Requirements

  • Strong ML systems and inference knowledge, including profiling and benchmarking models, working with traces, and building to technical specifications
  • Demonstrated ability to own a customer relationship end to end, with the communication skills to work directly with technical stakeholders
  • Comfort operating from incomplete specifications and driving work to completion independently
  • Experience in a startup or other fast-moving engineering environment
  • Based in, or willing to relocate to, San Francisco for a fully onsite role
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