Staff Forward Deployed AI Engineer | San Diego, CA

Staff Forward Deployed AI Engineer San Diego, CA · Hybrid · Full-Time About Cadre AI 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. The Role 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 energiz [... source excerpt omitted ...] ping the system yourself. What You'll Do 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 ove [... source excerpt omitted ...] orkflows, 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