AI Field Engineer - Enterprise

I_Call international (in partnership with AI Talent Hunt)I_Call international in partnership with AI Talent Hunt, is conducting a confidential search on behalf of a rapidly growing AI infrastructure company.AI Field Engineer - EnterpriseFull-time Remote: San Mateo, CA $176K - $224K (OTE: $220K - $280K)Seniority3+ 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 experienceShipped 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 featuresHard skillsLLM 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 workloadsSoft skillsDemonstrated executive presence in enterprise customer-facing roles Navigated enterprise org politics end-to-end — champions, detractors, security reviews, and procurement cyclesMiscellaneousDomestic travel to enterprise customers as neededTraits to avoidLLM experience limited to closed-model API wrappers with no exposure to open-model inference, serving frameworks, or fine-tuning Pure advisory/consultant profiles without shipping production code Pure Big Tech backgrounds with no startup or fast-paced field engineering exposureAbout this roleWe are looking for an AI Field Engineer (Enterprise) with 3+ years of experience to embed with our most ambitious enterprise customers and turn complex GenAI challenges into production systems — fast. You will 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 • Build end-to-end POCs and production integrations hands-on inside customer environments, navigating infrastructure, security, and organizational constraints • Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation frameworks to scale from exploration to production • Manage multi-stakeholder enterprise relationships — identifying champions, navigating org politics, and aligning stakeholders • Feed customer pain points and deployment patterns back into the engineering roadmapKey Requirements• Deep hands-on experience with LLM inference and/or training (vLLM, SGLang, TensorRT-LLM) • Strong experience with fine-tuning workflows (SFT required; DPO/RFT a plus) • Proven ability to ship production code inside customer environments • Strong Python + GPU/cloud experience (AWS, Azure, or GCP) • Kubernetes proficiency • Executive presence across technical and business stakeholders • Pre-sales or customer-facing field engineering experience requiredSalary$176K - $224K (OTE: $220K - $280K) (80/20 base/variable split, paid quarterly based on performance. Equity included separately. Compensation scales with experience; senior candidates may exceed range.)EquityCompetitive equityVisa sponsorshipH-1B transfers and TN visas sponsored. O-1 considered case-by-caseRemote work policyUS-based, remote-friendly Requires regular travel to enterprise customers Hybrid model may apply near hubsLocationSan Mateo, CA, New York, NYTech stackPython, 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 frameworksWhat to ask candidates• What specifically about this role excites you? • How do you partner with sales in large enterprise deals? • Are you open to office collaboration in San Mateo or New York? • Walk through a production POC you built inside a customer environment • Experience with vLLM, SGLang, SFT, DPO workflows • Salary expectations • Current job search statusIdeal candidates & backgroundsAI-native inference / LLM infrastructure companies"Together AI" OR "Replicated" OR "Modal Labs" OR "Baseten" OR "Anyscale" OR "Groq" OR "Cerebras" OR "Mistral AI" OR "Cohere"Hyperscaler AI & cloud infrastructure"Microsoft" OR "Google" OR "Amazon Web Services (AWS)" OR "NVIDIA" OR "AMD" OR "Databricks" OR "Snowflake" OR "MongoDB"AI-native developer tools & applied AI companies"Cursor" OR "Notion" OR "Scale AI" OR "Weights & Biases" OR "Hugging Face" OR "LangChain" OR "Pinecone" OR "Weaviate" OR "Glean" OR "Perplexity AI"