Forward Deployed Engineer Jobs in San Francisco

Looking for a forward deployed engineer job in San Francisco? Choose from 45 open roles at 30 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.

45 Open roles
30 Companies hiring
257K Average salary

What do Forward deployed engineers in San Francisco work on?

Most of the sample titles and summaries describe engineers who embed with external customers to design, build, and hand off production AI systems — writing code, shipping agents, and tuning models rather than sitting in a pre-sales or account management function. Day-to-day work spans fine-tuning open-weight language models, building evaluation infrastructure, integrating LLM APIs into enterprise workflows, and owning deployments from technical discovery through to production handoff.

The OpenAI healthcare role illustrates domain specialisation, requiring knowledge of EHR systems and interoperability standards. The Databricks senior role centres on data engineering and platform architecture across cloud providers. Reflection AI's post-training role focuses on dataset preparation and fine-tuning techniques such as SFT and DPO. At the management end, the Amazon senior manager role involves leading large multi-team engagements and communicating technical strategy to executive stakeholders, while the Baseten engineering manager role blends hands-on LLM inference work with team leadership.

Skills and experience employers ask for

The skills counts reflect how often each term appears in posting descriptions across the full set on this page, not formal requirements. Evaluation and LLMs appear in the majority of postings; Python and APIs appear in roughly half. Agent-related skills appear in a substantial minority. Infrastructure tooling — AWS, CI/CD, TypeScript, Kubernetes, Docker, GCP, Azure, SQL — is mentioned in a smaller subset, suggesting it matters for some roles but is not universal.

Evaluation 67%
LLMs 60%
Python 56%
APIs 53%
Agents 42%
AWS 20%
CI/CD 18%
TypeScript 16%
RAG 13%
Kubernetes 13%
Docker 13%
GCP 13%
Azure 13%
SQL 13%

Forward Deployed Engineer roles that state a salary

The employers' own advertised ranges, for individual roles at different levels — not an average and not a market rate.

San Francisco office, hybrid or remote?

On-site working is the most common arrangement stated in these postings, making up the clear majority. A sizeable minority specify hybrid working. Only a very small number are listed as fully remote. No postings left work mode unstated, which is relatively unusual and means candidates can take the stated modes at face value for initial filtering. Where a role is on-site or hybrid, the expectation of customer travel is mentioned explicitly in at least one sample summary, so candidates should check individual postings for travel requirements beyond the primary work location.

Make your application specific to the work

  1. Check role type carefully Titles on this page span individual contributor, lead, manager, and director levels, and a large portion do not signal seniority in the title itself. Read the experience requirements in each posting before applying, as the gap between a four-year IC role and a ten-year multi-team manager role is significant.
  2. Prepare a technical deployment example The sample summaries consistently ask for evidence of shipped, production-grade AI work — fine-tuned models, deployed agents, or end-to-end customer integrations — so have a concrete example ready that covers the full lifecycle from scoping to handoff.
  3. Match your stack to the posting Skills mentioned vary considerably across postings: some emphasise data platform work with Spark and cloud providers, others focus on LLM inference or post-training pipelines. Tailor your application materials to the specific technical context of each role rather than applying a single version.
  4. Clarify travel and location expectations Several postings involve customer travel that is separate from the primary work-location arrangement, and the extent of that travel is not always clear from the listing alone. Confirm the expected travel frequency at the earliest stage of the process.

Questions about Forward Deployed Engineer jobs in San Francisco

Only a minority of postings on this page include advertised pay. Among those that do, individual contributor ranges start as low as the low-to-mid six figures and extend well above three hundred thousand dollars at the upper end for senior or specialised roles. The ranges vary considerably by employer and seniority, so the advertised figures are best compared posting by posting rather than treated as a market-wide benchmark.

A very small number of postings on this page are listed as remote. The majority are on-site, with a meaningful portion hybrid. If remote working is important to you, filter explicitly for it, as most of these roles do not offer it.

LLMs and evaluation are mentioned in the majority of postings, and several sample summaries explicitly require production experience with language models, fine-tuning, or AI system deployment. That said, some roles focus more on data engineering or platform architecture. The technical depth required for AI specifically depends on the individual posting.

Visa sponsorship eligibility is not stated in the fact pack for these postings. You would need to check each employer's application process or job posting directly to find out.

Seniority is explicitly stated for roughly half the postings on this page, covering senior, lead, manager, and director levels. The remaining postings do not signal seniority in the available data. Where it is not stated, the years of experience required in the job description is the most reliable indicator.

Jobs checked 1 day ago. · Guide reviewed 9 September 2026.