AI Architect; Mid-Level

Position: 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 product ionizing 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, Info Sec, 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 change logs, 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