# AI Field Engineer, AI Infrastructure (Remote - US) at Lavendo > United States · Unspecified · DevOps / SRE / Infra · open. Source: https://alderhq.app/jobs/ashby%3Alavendo%3Ac8917cc4-272f-4eb3-a159-e33fc04cd89d (read 2026-11-09). ## Facts (observed) - Company: [Lavendo](https://alderhq.app/companies/lavendo) - Location text: San Mateo; New York - Where it can be done from (inferred): United States (evidence: "Location: San Mateo; New York") - Posted: 2026-08-03 (98 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/lavendo/c8917cc4-272f-4eb3-a159-e33fc04cd89d - Skills listed (inferred): Python, AWS, GCP, Azure, Kubernetes, SQL, LLMs ## Pay and sponsorship - Posted pay: $220k–$280k per year (from the listing's pay field) - Market band for similar posted roles (SF Bay Area, n 181): p25 $200k, median $238k, p75 $300k ## Description (the employer's text) Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit. ### About the Company Our client is a fast-scaling AI infrastructure company that helps enterprises and AI-native startups build, fine-tune, and serve their own specialized AI models — no more relying on someone else's black-box API. Their platform runs in production for some of the most recognizable names in tech, spanning text, image, embedding, audio, and multimodal workloads. Freshly backed by a Series D at a $17.5B valuation, this is a company with real scale, real customers, and real momentum behind it. ### The Mission They believe the next generation of great products will be built by companies that own their AI stack, not just rent it. Their mission is making open-model AI infrastructure genuinely fast, flexible, and production-grade for the teams building at the frontier. ### The Opportunity This is a forward-deployed engineering role where you're never far from either a terminal or a whiteboard with a VP on it. You'll work directly with VP Engineering, Head of AI/ML, and CTO-level partners at Fortune 500 enterprises and cutting-edge AI-native startups, owning the technical win from the first discovery call all the way through production. Two tracks are open — Enterprise and AI-Native — same role, different customer base, and we'll talk through which fits your background and interests best. ### What You'll Do Run the full pre-sales field cycle yourself: discovery, POC scoping, model evals, and final model selection Ship real production code inside customer environments — this is hands-on building, not advisory slides Deploy and fine-tune open-model LLMs using frameworks like vLLM, SGLang, and TensorRT-LLM (SFT baseline, DPO/RFT a big plus) Act as a true partner to your sales counterpart, shaping deal strategy rather than just supporting it Build relationships across a customer's org, from engineers to executives, and know how to move a deal forward on both levels ### What You Bring 3+ years in a client-facing AI/ML role — Solutions Architect, Forward-Deployed Engineer, Customer Success Engineer, Applied AI Engineer, Sales Engineer, or an AI/ML-focused SWE with genuine customer exposure Real hands-on experience with open-model LLM inference and/or fine-tuning Hyperscaler experience in an AI context (AWS, Azure, or GCP) Strong Python skills, comfort with GPU infrastructure and Kubernetes A background at an AI-native company or a SaaS company genuinely building AI features (not bolting them on) Full-time work history, and openness to travel to enterprise customers as needed ### Key Success Drivers You're the rare person equally comfortable debugging inference trade-offs with an ML engineer in the morning and presenting the same trade-offs to a VP by afternoon. You bring genuine customer obsession alongside technical depth — this role rewards people who've shipped things themselves, not just advised on them. Strong candidates own outcomes end-to-end and know how to build trust across both engineering and executive stakeholders. ### Why Join? ### Compensation & Equity Base salary $176K–$224K, OTE $220K–$280K Performance-based variable compensation, paid quarterly Meaningful equity in a fast-growing, well-funded startup — Series D at a $17.5B valuation ### Location Remote-friendly with hubs in New York and San Mateo — flexibility to work from anywhere in the US with regular travel to enterprise customers ### Visa Sponsorship Details Open to visa transfers (e.g. OPT, H1B transfers) Open to visa sponsorships (e.g. new H1B, TN) ### Benefits Comprehensive benefits package ### Interviewing Process Recruiter/hiring manager screen (30 min): logistics, motivation, fit Take-home (5 days): build a working text-to-SQL system Culture + live coding (45 min): product discussion, extend your code live Discovery + hiring manager (45 min): live discovery role-play --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Alavendo%3Ac8917cc4-272f-4eb3-a159-e33fc04cd89d and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.