Field AI Engineer

Actively Reviewing the Applications

JFrog

India Full-Time On-site

Posted 2 days ago • Apply by June 14, 2026

Job Description

At JFrog, we’re reinventing DevOps to help the world’s greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if you’re willing to do more, your career can take off. And since software plays a central role in everyone’s lives, you’ll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust JFrog to manage, accelerate, and secure their software delivery from code to production -- a concept we call “liquid software.” Wouldn't it be amazing if you could join us in our journey?

Most engineers sit behind a desk. This one doesn't.

As our Field AI Engineer, you'll be embedded in the San Francisco AI ecosystem: attending meetups, demos, hackathons, and industry events where practitioners are doing interesting work. You'll need technical depth to hold substantive conversations with researchers and engineers, and enough curiosity to consistently come away having learned something useful.

This role is modeled on the Forward Deployed Engineer archetype pioneered by companies like OpenAI and Anthropic, but with a twist. Where traditional FDEs embed with a single customer, you embed with the entire ecosystem. Your customer is the SF AI community. Your deliverable is intelligence.

You'll represent our company as a peer, not a pitch. Everything you learn (the tools gaining traction, the patterns that are working, the problems enterprises keep running into) feeds directly back into our product, strategy, and roadmap.

As a Field AI Engineer in JFrog you will...

Field Intelligence & Ecosystem and Community Scanning

Attend AI meetups, research demos, hackathons, and conferences across the SF Bay Area as a consistent, trusted presence
Build a structured view of the AI vendor and startup landscape — what's emerging, what's enterprise-ready, what's overhyped
Run a regular intelligence loop: weekly signal briefs, monthly deep-dives for leadership, and ad hoc alerts when something important surfaces
Identify and track tools, frameworks, and architectural patterns gaining real adoption before they become mainstream

Deep Community Relationships

Build authentic relationships with AI researchers, startup founders, enterprise architects, and practitioners — as a peer, not a vendor
Become a known and trusted voice in the SF AI scene; someone people want to loop in, not avoid
Maintain a living network map of who's building what, who's thinking about what problems, and where the interesting work is happening

Technical Credibility & Hands-On Evaluation

Get hands-on with new tools, APIs, and agentic frameworks — prototype and evaluate them firsthand before forming a view
Engage credibly in deep technical conversations about LLMs, RAG architectures, agentic systems, fine-tuning, prompt engineering, and enterprise AI infrastructure
Produce concise technical evaluations: what a tool does, how it works, where it breaks, whether it matters for enterprise

Internal Amplification

Act as the connective tissue between the external AI world and our internal teams — product, engineering, and leadership
Run regular internal "what's new in AI" sessions to keep the team sharp and ahead of the curve
Partner with product to ensure field learnings shape our roadmap; partner with GTM to sharpen competitive positioning
Occasionally write or speak externally, not on a content treadmill, but when you have something genuinely worth saying

To be a Field AI Engineer in JFrog you need...

Technically deep: you've built real things with AI. You can evaluate a new tool in an afternoon, spot architectural tradeoffs immediately, and hold your own in any technical conversation
Genuinely embedded: you're already showing up at SF AI events, or you will be within 30 days of starting. You find energy in these rooms, not obligation
A strong synthesizer: you can take a noisy week of conversations and distill it into three things that actually matter
Enterprise-aware: you understand what it means to deploy AI inside a large organization: procurement, security, integration complexity, change management, organizational politics
Inbound-first: you're more interested in what you can learn from a conversation than what you can say in it
Love bringing the signal back: you enjoy translating external learnings into insights the organization can act on

Qualifications

4+ years in a technical hands-on role: engineering, ML, solutions engineering, forward-deployed engineering, or similar
Hands-on experience with modern AI/ML tooling: LLMs, RAG pipelines, agentic frameworks (LangChain, LlamaIndex, AutoGen, or equivalent)
Strong Python skills; comfort with APIs, cloud infrastructure, and developer tooling
Demonstrated presence in the AI community — meetups, open-source, writing, speaking, any of it
Based in San Francisco or willing to be deeply embedded here

Nice to Have

Prior experience in a forward deployed, field engineering, or developer relations role
An existing network in the SF AI/ML ecosystem
Familiarity with enterprise software procurement and IT buyer personas
Public writing, a newsletter, or a following in the AI space

The best Field AI Engineer isn't the loudest voice in the room. It's the one who leaves every conversation knowing more than when they walked in, and has the judgment to know what to do with it.

What Jfrog Can Offer…

At JFrog, base salary is only one component of our compensation package.
This position also includes an equity package of restricted stock units (RSU). In addition, JFrog employees are eligible to participate in our Employee Stock Purchase Plan.
JFrog provides employees comprehensive benefits including medical, dental, vision, retirement, wellness and much more!

JFrog is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status or any other category protected by law.