AI Architect (Mid-Level)

Overview

We're looking for a mid-level AI Architect to help us execute NAPA's in-house AI strategy in a contract-to-hire capacity. NAPA is shifting from a buy-only AI model to a buy-and-build model, and this person is a direct execution partner to AI leadership — helping stand up the capability, not just advise on it.

This is not a traditional ML or model-training role. We're not building foundation models or doing deep research. We're taking real internal prototypes and pushing them to production, designing agent-based solutions around NAPA-specific workflows, and establishing the infrastructure, patterns, and playbooks to do this repeatably.

The ideal person is technically strong, builds on the side, and lives in the current AI landscape — experimenting with coding agents like Claude Code and Codex, wiring up agent frameworks on weekends, and learning as fast as the space is moving.

What You'll Do

• Execute on NAPA AI Strategy — partner directly with AI leadership to stand up our in-house AI capability, starting with productionizing existing internal prototypes

• Architect and build AI-enabled solutions using modern LLMs, agent frameworks, and AI-assisted development tooling (Claude Code, Codex, Cursor, and similar)

• Design agent-based systems — orchestration, tool use, memory, guardrails, evaluation, and human-in-the-loop patterns

• Take prototypes to production — turn internal builders' working prototypes into production-grade solutions with real infrastructure, security, and monitoring

• Help establish the build playbook — infrastructure patterns, development stack, security posture, and repeatable processes so NAPA can ship AI solutions as a capability, not a one-off

• Translate business problems into pragmatic AI architectures — lean on the right tool for the job rather than over-engineering

• Collaborate across the org — work with engineering, InfoSec, product, and business stakeholders to make sound technical decisions and move work forward

• Evaluate emerging tools and patterns — and recommend where they fit (or don't) based on real experimentation, not hype

• Share the AI expertise load — act as a credible, independent technical partner so AI knowledge isn't concentrated in one person

What We're Looking For

• 4–8 years of experience in software engineering, systems design, or technical architecture

• Strong architectural mindset grounded in hands-on engineering — you understand tech stacks, APIs, services, data flow, and what production-grade actually means

• Deep fluency with the current AI landscape, including:

• LLMs and AI-powered APIs (OpenAI, Anthropic, open-source)

• Agent-based architectures, orchestration frameworks, and tool use patterns

• AI-assisted coding tools (Claude Code, Codex, Cursor, etc.) — not just as a user, but as a builder

• Modern AI tooling and platforms, commercial and open source

• Demonstrated self-directed experimentation — side projects, personal agents, weekend builds, hack repos. Evidence that you build with this stuff because you want to, not just because you're paid to.

• A "dangerous enough" posture — confident designing and shipping AI solutions without needing to be a top-tier ML researcher

• Genuine curiosity and a habit of staying current — you read the changelogs, try the new tools, and form opinions

• Clear communicator who can explain technical decisions to non-technical stakeholders

• Nice to Have (Not Required)

• Experience integrating AI into existing enterprise applications or workflows

• Exposure to cloud platforms (AWS, Azure, GCP)

• Background with APIs, microservices, or distributed systems

• Prior experience in an architect, senior engineer, or technical lead role

• Experience in regulated or enterprise contexts (healthcare, finance, clinical data)

• What This Role Is Not

• Not a research-focused ML role — we're not training foundation models

• Not a role for someone who wants to stay in notebooks or stay on the buy side

• Not a pure oversight or advisory role — this is hands-on build work

• Not looking for a top-tier AI scientist or cutting-edge ML specialist

• Engagement Details

• Contract-to-hire — with a clear path to full-time based on performance and fit

• Mid-level scope with room to grow into the core in-house AI capability at NAPA

• Emphasis on practical application, experimentation, execution, and continuous learning

• Works directly with AI leadership on first-priority NAPA Nexus build initiatives