Forward Deployed Engineer

Deep Infra

$150K — $195K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in customer-facing engineering with a successful technical outcome.
  • Strong proficiency in Python programming.
  • Ability to communicate effectively with both technical and non-technical audiences including engineers and CFOs.

Responsibilities

  • Own the technical win and manage the POC timeline from the initial call.
  • Design and implement reproducible benchmark tests for various performance metrics.
  • Conduct competitive bake-offs against top AI providers to secure deals.
  • Optimize model-to-hardware deployments on specified NVL72 systems.
  • Create cost-per-token models and develop migration strategies.
  • Manage enterprise security compliance reviews and ensure deployment readiness.
  • Produce reusable benchmark reports and enablement materials for the account executive team.

Benefits

  • Opportunity to shape and define the Forward Deployed Engineering function from its inception.
  • Direct collaboration with co-founders and the inference engineering team on key deals.
  • Be part of a small, agile team that values quick execution and customer feedback.
  • Engage in significant projects that influence how enterprises adopt leading open-source AI solutions.
Full Job Description
Why this role matters

As DeepInfra's enterprise pipeline grows, our customers need a technical partner who can run rigorous evals, defend benchmarks, and speak fluently to both engineering and procurement - someone who can own the technical win from first call through production.

This is a pioneering role. You'll work closely with Sales, our co-founders, and the engineering team on the deals that matter most. You'll own the technical win end to end: running head-to-head bake-offs against leading AI providers, tuning deployments on the latest hardware, and turning what you learn into reusable assets that make every future deal faster to close. As our first FDE, you'll also define what the function looks like as GTM scales.

What You'll Do

  • Own the technical win and the POC timeline, working closely with Sales and Engineering, from call one.
  • Design and run reproducible benchmark harnesses (TTFT, ITL, throughput/GPU, p95/p99) and quality-parity evals.
  • Run head-to-head bake-offs against leading AI providers - and win them.
  • Tune model-to-hardware deployments on B200/B300/GB300 NVL72.
  • Build cost-per-token models and write migration plans.
  • Handle enterprise security and compliance review, and get deployments to launch readiness.
  • Own account health post-signature, driving usage reviews and expansion.
  • Turn what you learn into reusable benchmark reports, reference architectures, and AE enablement material.


What You Bring

  • Customer-facing engineering with an owned technical outcome at an infrastructure or ML platform company.
  • Strong Python skills.
  • Dual-audience presence with commercial instinct - credible with a skeptical staff engineer, clear with a CFO, and able to tell a technical objection from a procurement one.


Bonus

  • Hands-on experience with inference internals: vLLM, SGLang, or TRT-LLM, batching, KV cache math, quantization.
  • Experience with agentic or coding-assistant workloads at scale.
  • Prefix-cache-heavy long context workloads.
  • Diffusion image/video, ASR/TTS, or multi-LoRA serving.
  • Open-source contributions to vLLM or SGLang.
  • Deep NVLink/InfiniBand topology knowledge.


Why DeepInfra

  • Define DeepInfra's Forward Deployed Engineering function from day one and have a direct impact on its direction.
  • Work directly with co-founders and the inference team on the deals that matter most.
  • Join a small, high-performing team where your work ships quickly and reaches customers around the world.
  • Help shape how enterprises adopt some of the world's leading open-source AI models.


How we work

Three traits define the people who thrive here, and this role leans on all three.

Initiative. We take ownership and step in where we can add value. Whether it's starting something new, improving what exists, or helping move ideas forward, we aim to be proactive and thoughtful in how we contribute.

Drive. We're energized by hard problems. Building AI infrastructure is complex, and we lean into that. We care about doing things well, moving fast, and continuously improving - because solving meaningful challenges is what motivates us.

Grit. Things don't always work on the first try - and that's expected. We stay persistent, adapt quickly, and learn as we go. We take setbacks seriously, but not personally, and use them to get better.

Compensation

The base pay range for this role is $150,000 - $195,000 per year.

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