Lead and mentor a San Diego engineering team while staying hands-on building production LLM systems (RAG, agents, document processing). Drive architecture, evaluate models and tooling, own end-to-end delivery, collaborate with clients, and create reusable internal tooling and best practices to improve team performance and client outcomes.
Staff Forward Deployed AI Engineer
About Cadre AI
The Role
What You'll Do
What You Need to Succeed
Why Cadre AI
Compensation
San Diego, CA · Hybrid · Full-Time
Cadre AI is an AI strategy and integration firm that builds production AI systems for B2B companies in private equity, wholesale lending, real estate, and SaaS. We do not build decks about what AI could do. We ship systems that move revenue, compress costs, and automate the work that used to take entire teams.
As Staff AI Engineer, you are the technical leader and backbone of Cadre's San Diego engineering team. At this level, your job is no longer just what you build; it is making sure every engineer around you builds better. You mentor and manage engineers, set the standard for how the team designs, reviews, and ships AI systems, and own their growth as deliberately as you own your own code.
You pair that leadership with serious technical depth. You stay hands-on with the hardest builds in our client portfolio: multi-step agent systems, complex document processing pipelines, and automations that touch core revenue operations. When a problem has ambiguous requirements or no obvious solution, the team looks to you, and clients measure the result in EBITDA impact, not demos.
You report to the Head of Client Engineering, and you will occasionally join client calls to walk stakeholders through what we are building and why. You thrive here if leveling up the people around you energizes you as much as shipping the system yourself.
You are on the forefront of the technology, reimagining how Cadre does AI and delivering the high-value solutions that set us apart with clients.
Team Leadership and Mentorship
- Manage and mentor two engineers on the San Diego team, owning their technical growth, code quality, and delivery.
- Set the engineering bar through rigorous code review, pairing, and reference implementations the rest of the team builds on.
- Serve as the first escalation point when engineers hit problems they cannot solve alone, teaching as you unblock.
- Build the habits, patterns, and practices that make every engineer on the team measurably better quarter over quarter.
Technical Direction
- Drive architecture decisions across client builds: agentic workflows, RAG pipelines, document processing, and automation running in production.
- Evaluate new models, frameworks, and techniques as they emerge, and decide what enters Cadre's production toolkit.
- Turn hard-won lessons from client builds into reusable internal tooling, templates, and documentation that compound across engagements.
Build and Ship Production AI Systems
- Stay hands-on with Cadre's most complex client systems, owning delivery end to end from LLM orchestration and evaluation to data pipelines, APIs, and cloud infrastructure.
- Make pragmatic build decisions under real constraints: client timelines, legacy systems, messy data, and measurable business outcomes on the line.
- Ship fast without sacrificing reliability; design systems that keep working long after the engagement ends.
Client Collaboration
- Join client calls when the conversation needs technical depth, walking stakeholders through system designs, trade-offs, and progress.
- Translate ambiguous business problems into concrete system designs and delivery plans clients can commit to.
- Flag risks, trade-offs, and scope realities directly and early, protecting both the client outcome and the team's delivery.
- 8+ years of software engineering experience, including 2+ years building LLM-powered systems (RAG, agents, structured extraction) that run in production, not just prototypes or internal experiments.
- Demonstrated technical leadership: engineers you have mentored or managed got measurably better because of your code review, pairing, and guidance, and you want direct reports as part of your role.
- Expert-level Python and strong full-stack fundamentals, with the judgment to choose boring, reliable technology when the problem calls for it.
- Production cloud experience (AWS, GCP, or Azure), including deploying, monitoring, and maintaining systems that clients depend on daily.
- Deep working knowledge of the modern AI stack: prompt and context engineering, evaluation, embeddings, vector search, and agent orchestration frameworks.
- A track record of owning ambiguous, high-stakes projects end to end, from problem framing through architecture, build, and post-launch iteration.
- Fluent English and clear communication on client calls; you can explain an architecture decision to a non-technical executive without losing them.
- Consulting-environment adaptability: comfort switching between client contexts, industries, and codebases without losing momentum.
- Based in San Diego, CA with reliable overlap with Colombia business hours for client and team collaboration.
- An AI-first working style: you use these tools daily to multiply your own output and teach the team to do the same.
- Real leadership. You will be the technical backbone of a growing engineering team, with engineers who level up because of you and the autonomy to make the calls that matter.
- AI-native culture. We do not just build AI for clients. We use it to run our own operations. You will work with people who are as obsessed with the tools as you are.
- Access to the frontier. Through partnerships with Anthropic and OpenAI, you will be among the first to experiment with new models and capabilities.
- Upside. We are bootstrapped, profitable, and growing fast. Early team members share in the success they help create.
- No bureaucracy. Small teams. Clear accountability. The best idea wins, regardless of who says it.
If you want your next five years to be measured in systems running in production, businesses that work differently because you shipped, and a team of engineers who are better because you led them, this is that role.
The base pay range for this role is $165,000 – $200,000 per year.
Similar Jobs
Fintech • Financial Services
Provide personalized, roving branch support across multiple locations: handle account openings, teller transactions, service requests, and credit applications. Build customer relationships, promote products, use digital tools, adhere to compliance and risk controls, and coordinate referrals to licensed specialists. Travel across assigned geography and support branch operations and growth.
Fintech • Financial Services
Grow and manage relationships with affluent customers, acquire new clients, and deliver multi-product financial advice. Own a book of business, coordinate referrals with Wealth/Home Lending/Business Banking, support digital adoption, handle everyday banking and service requests, and maintain risk/compliance and licensing requirements.
Fintech • Financial Services
Manage and grow a portfolio of affluent customers through proactive outreach, discovery-driven advice, and multi-product financial solutions. Coordinate with Wealth, Home Lending, and Business Banking, handle everyday banking needs, ensure compliance and documentation, and drive digital adoption to deepen relationships and deliver measurable retention and growth.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
