AI Engineer Jobs in San Francisco, CA
AI Engineer jobs in San Francisco concentrate in SoMa, Mission Bay, and the Financial District, with strong demand from enterprise tech, biotech, and fintech employers, and openings from early-career to staff-level roles. Companies currently hiring include RNB Consultancy, Capital One, and BRAIN. Scan the live roles below and apply to whichever ones fit.
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About Tolmo
Tolmo is cybersecurity for the age of AI. Coding agents now ship software faster than any human team can review or secure it; 100+ pull requests per engineer per week is no longer an outlier, and attackers are using the same agents to find and exploit weaknesses in days, not months. The old playbook of quarterly pentests and endless alert queues breaks at this speed.
We're building a new security playbook. Tolmo runs a fleet of AI security agents that reason over a live graph of your entire production system (code, CI, cloud, and telemetry) and continuously attack a faithful copy of it like a real adversary. Every finding arrives validated, with its blast radius and a remediation plan that lands in your workflow, ready for a coding agent to fix. Hours to integrate, days to your first validated finding.
We've done this before: Tolmo's founders built Sqreen (acquired by Datadog) and led security products that thousands of organizations trusted. We're backed by Accel and Y Combinator and just getting started.
The role
Our product is only as good as our agents' judgment. As a Research Engineer on AI Security, you make that judgment better and measurably so: how our agents plan, reason over a graph of a customer's production system, decide what is worth testing, and know when a finding is real.
This sits between research and engineering. In one week you might design an eval that catches a new class of false positive, change how an agent plans a multi-step investigation, compare models on a hard benchmark, and harden the agents themselves against prompt injection from the systems they inspect. You'll work directly with the founders, our engineers, and the security leads who run pentests with our agents, and your work ships to production.
What you'll do
Agent reasoning: improve how our agents plan, use tools, and reason over a live graph of code, cloud, and telemetry, so they reach real findings faster and with fewer dead ends.
Evaluation: build the evals, benchmarks, and graders that tell us whether an agent actually got better, and make them part of how every change ships.
Model selection and tuning: compare models, prompts, and agent designs on cost, latency, and quality, and turn the results into production decisions.
Model and agent security: defend our agents against prompt injection, data exfiltration, and manipulation by the very systems they test, and research the security of LLM-based applications our customers build.
Reliability at scale: make long-running agents dependable across thousands of runs: verification, self-checks, and sensible stopping.
Learning from the field: study agent runs from customer engagements, find where reasoning broke, and turn each failure into an eval and a fix.
What we're looking for
Hands-on experience building, evaluating, or improving LLM-based agents or systems in production.
A rigorous, empirical approach: you design experiments, distrust single anecdotes, and let the evals decide.
Strong engineering skills: you write production-quality code (Python, TypeScript, or Go) and build tools other people rely on.
A working understanding of security, or a strong drive to learn it fast: how real systems are attacked and how findings are validated.
Familiarity with LLM security risks such as prompt injection, jailbreaks, and tool misuse.
You build with AI coding agents daily (e.g., Claude Code, Cursor) and have opinions about what makes them reliable.
Nice to have
Research background in machine learning, AI safety, or security: publications, open-source work, or talks.
Offensive security experience: penetration testing, red teaming, bug bounty, or CTFs.
Experience with reinforcement learning, fine-tuning, or synthetic data generation for agents.
Experience with graph data models or reasoning over structured data.
Prior early-stage startup experience.
Compensation & benefits
Competitive salary, depending on level and experience.
Early-stage equity: you're joining early; you'll own a real piece of what we build.
Comprehensive medical, dental, and vision coverage, and the equipment you need to do your best work.
Based in San Francisco; we work in person.
Tolmo is building a team with wide-ranging backgrounds, perspectives, and paths into security; we think it makes our product and judgment better. If you're excited about this role but don't match every point above, we'd still like to hear from you. We're an equal opportunity employer and welcome applicants of every background.
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Find AI Engineer JobsAI Engineer Job Market in San Francisco
Who's Hiring
- RNB Consultancy95R
- Capital One50

- BRAIN45

- David Joseph & Company34D
- OpenAI28

Top Industries Hiring
- Technology & Software157
- Banking & Financial Services34
- Science & Research28
- Electronics & Hardware11
- Retail6
AI Engineer Jobs in San Francisco: Frequently Asked Questions
How do I get a ai engineer job in San Francisco?
Focus your search on SoMa, Mission Bay, and the Financial District, where enterprise tech platforms, AI-native startups, and large biotech firms concentrate most of their engineering hiring. Candidates with hands-on experience in LLM fine-tuning, MLOps pipelines, or production model deployment stand out in this market. Building a portfolio on public datasets and contributing to open-source projects helps differentiate you with San Francisco employers who review GitHub activity closely.
Which companies hire ai engineers in San Francisco?
Companies currently hiring ai engineers in San Francisco include RNB Consultancy, Capital One, and BRAIN, per current listings on Migrate Mate as of November 2026. San Francisco's employer mix ranges from AI-native startups to large enterprise software and biotech firms, many of which maintain dedicated applied AI or machine learning teams.
Are there remote ai engineer jobs in San Francisco?
Yes, though roles involving on-site infrastructure, lab hardware, or embedded systems typically require in-person presence. About 61% of ai engineer openings tied to San Francisco are remote or hybrid as of November 2026, with most flexible arrangements concentrated in software-side work such as model development, evaluation, and API integration rather than hardware-dependent or research-lab positions.
How can I get a ai engineer job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is targeting AI-native startups in SoMa and Mission Bay that hire junior ML engineers or AI operations associates to support model evaluation and data pipeline work. Contract and project-based roles at early-stage companies often convert to full-time. Building a focused portfolio around a single application domain, such as NLP or computer vision, and attending local AI meetups in the city gives early-career candidates a concrete edge.
Which industries hire the most ai engineers in San Francisco?
San Francisco ai engineer roles concentrate in Technology & Software, Banking & Financial Services, and Science & Research, based on current listings on Migrate Mate as of November 2026. San Francisco's unique density of AI-native product companies, enterprise software vendors, and biotech research organizations creates sustained cross-sector demand that keeps hiring active across economic cycles.
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