Staff Forward Deployed AI Engineer | San Diego, CA

Go Cadre • San Diego, CA

97d • Hybrid

About The Position

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. The Staff Forward Deployed AI Engineer is the technical leader of Cadre’s San Diego engineering team, combining hands-on development of complex client systems with leadership and mentorship of two engineers. The role sets standards for how the team designs, reviews, and ships AI systems and takes responsibility for engineers’ technical growth.

The engineer leads architecture decisions for agentic workflows, RAG pipelines, document processing, and production automation; evaluates emerging models and frameworks; and turns lessons from client work into reusable tools, templates, and documentation. They own complex systems end to end, spanning LLM orchestration and evaluation, data pipelines, APIs, and cloud infrastructure, while making pragmatic decisions amid client timelines, legacy systems, and messy data.

The role also involves client collaboration: translating ambiguous business problems into system designs and delivery plans, explaining technical choices and progress to stakeholders, and raising risks and scope trade-offs early. The position is based in San Diego, California, is hybrid and full-time, and reports to the Head of Client Engineering. Reliable overlap with Colombia business hours is required.

Requirements

• At least 8 years of software engineering experience, including at least 2 years building production LLM-powered systems such as RAG, agents, or structured extraction.
• Demonstrated technical leadership, including mentoring or managing engineers and a desire to have direct reports.
• Expert-level Python skills and strong full-stack fundamentals.
• Production cloud experience with AWS, GCP, or Azure, including deploying, monitoring, and maintaining systems.
• Deep working knowledge of prompt and context engineering, evaluation, embeddings, vector search, and agent orchestration frameworks.
• Experience owning ambiguous, high-stakes projects end to end, from problem framing through architecture, implementation, and post-launch iteration.
• Fluent English and clear communication on client calls, including the ability to explain architecture decisions to non-technical executives.
• Adaptability in consulting environments, including switching between client contexts, industries, and codebases.
• Based in San Diego, California, with reliable overlap with Colombia business hours.
• An AI-first working style, using AI tools daily to increase personal output and teach the team to do the same.

Responsibilities

• Manage and mentor two engineers on the San Diego team, owning their technical growth, code quality, and delivery.
• Set engineering standards through code review, pairing, and reference implementations.
• Act as the first escalation point for engineers facing difficult problems, teaching while unblocking them.
• Build team habits, patterns, and practices that improve engineering capability over time.
• Drive architecture decisions across client builds, including agentic workflows, RAG pipelines, document processing, and production automation.
• Evaluate emerging models, frameworks, and techniques and decide which become part of the production toolkit.
• Turn lessons from client projects into reusable internal tooling, templates, and documentation.
• Own delivery of complex client systems end to end, from LLM orchestration and evaluation through data pipelines, APIs, and cloud infrastructure.
• Make pragmatic build decisions under client timelines, legacy-system constraints, messy data, and business-outcome requirements.
• Ship reliable production systems that continue working after client engagements end.
• Join client calls to explain system designs, trade-offs, and progress to stakeholders.
• Translate ambiguous business problems into concrete system designs and delivery plans.
• Communicate risks, trade-offs, and scope constraints early and directly.

Benefits

• Early team members share in the success they help create.
• Access to new models and capabilities through partnerships with Anthropic and OpenAI.
• Autonomy and meaningful technical leadership in a growing engineering team.
• AI-native culture and small teams with clear accountability.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed