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Open nowFirst seen 2 days ago

AI Field Engineer - Enterprise

Cross Border Talents439 open roles

Where
San Mateo, California, United States, Remote
Work mode
Remote
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Your applicationOpen nowAI Field Engineer - EnterpriseCross Border Talents · San Mateo, California, United States, Remote

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 2 days ago

The posting

Job Description

AI Field Engineer - Enterprise

Employment Type: Full-time

Work Mode: Hybrid (US-based, remote-friendly)

Location: San Mateo, CA / New York, NY

Compensation: $176K - $224K Base (OTE: $220K - $280K)

Seniority: 3+ Years Experience

Seniority

  • 3+ years of experience in customer-facing AI/ML field engineering (FDE, Applied AI, Solutions Architect, AI Infra, ML Engineer, Software Engineer with pre-sales exposure, or research backgrounds transitioning to customer-facing roles)

Work Experience

  • Shipped AI/ML production code inside a customer's environment
  • Hands-on LLM inference and fine-tuning experience — ran SFT pipelines, benchmarked latency, and tuned open-model deployments
  • Ran the full field cycle in a pre-sales or customer-facing capacity — discovery, POC scoping, load tests, evals, and model selection
  • Background at an AI-native/AI-infra startup (inference, MLOps, developer tooling) or enterprise SaaS with built-in AI features

Hard Skills

  • LLM serving frameworks (vLLM, SGLang, TensorRT-LLM), agents, inference trade-offs, terminal-comfortable
  • Python and Kubernetes proficiency
  • Trained open models and familiar with fine-tuning methodologies (SFT, DPO, RFT)
  • GPU optimization for LLM workloads

Soft Skills

  • Demonstrated executive presence in enterprise customer-facing roles
  • Navigated enterprise org politics end-to-end — champions, detractors, security reviews, and procurement cycles
  • Miscellaneous
  • Domestic travel to enterprise customers as needed

About This Role

We are looking for an AI Field Engineer (Enterprise) with 3+ years of experience to embed with enterprise customers and turn complex GenAI challenges into production systems — fast. You'll be the technical tip of the spear, pairing deep hands-on engineering with the executive presence to earn trust across large organizations and drive deals from first discovery call to production deployment.

What Will You Be Doing?

  • Lead technical discovery calls, scope POCs, and run load tests and evaluations to validate the right model architecture and deployment configuration for each enterprise customer
  • Build end-to-end POCs and production integrations hands-on-keyboard inside customer environments, navigating their infrastructure, security requirements, and organizational constraints
  • Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation frameworks — moving them from open-model exploration to production at scale
  • Manage multi-stakeholder enterprise relationships — identifying technical champions, navigating org politics, and aligning the right people to move deals forward quickly
  • Feed recurring customer pain points and deployment patterns back into the product roadmap, acting as a direct feedback loop between the field and engineering

Requirements

Key Requirements

  • Deep hands-on experience with LLM inference and/or training — working knowledge of open-model frameworks (vLLM, SGLang, TensorRT-LLM) and fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus); candidates with only closed-model/API-wrapper experience will not clear the bar
  • Proven ability to ship production code inside a customer's environment — not just advisory work; you've built and deployed POCs/MVPs that ran in someone else's prod system
  • Strong Python skills plus GPU/cloud infrastructure experience (AWS, Azure, or GCP) and comfort with Kubernetes
  • Executive presence and enterprise navigation skills — able to run a technical deep-dive with an ML engineer and present architecture trade-offs to a VP in the same afternoon
  • Pre-sales or customer-facing field engineering experience (FDE, Applied AI Engineer, Solutions Architect, or similar); pure software engineers without customer-facing exposure are not a fit

Compensation & Benefits

  • Salary
  • $176K - $224K Base
  • OTE: $220K - $280K
  • Variable component paid quarterly based on individual and team performance
  • Compensation scales with experience
  • Candidates with 10+ years may be considered for above-range packages
  • Meaningful equity included on top of OTE

Equity

  • Competitive equity

Visa Sponsorship

  • H-1B transfers and TN visas sponsored
  • O-1 considered on a case-by-case basis

Remote Work Policy

  • US-based, remote-friendly
  • Offices in San Mateo, CA and New York, NY
  • Role requires regular on-site travel to enterprise customers
  • Hybrid policy (Mon/Wed/Fri in-office) applies for those based near a hub

Tech Stack

  • Python
  • vLLM
  • SGLang
  • TensorRT-LLM
  • Kubernetes
  • AWS
  • Azure
  • GCP
  • Azure AI Foundry
  • AWS Bedrock
  • AWS SageMaker
  • GCP Vertex AI
  • LLM Fine-Tuning (SFT, DPO, RFT)
  • GPU Infrastructure
  • Open-source LLM frameworks
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