Principal AI Engineer

Required

• 8+ years building production systems end-to-end (backend, frontend, integrations, infrastructure).
• Staff/Principal Engineer or Tech Lead experience, owning technical decisions on production systems.
• Shipped SaaS products with OAuth2, multi-tenancy, audit trails, and enterprise compliance.
• Deep AI/ML experience: production systems using LLM APIs (OpenAI, Anthropic, AWS Bedrock) and agent frameworks.
• Production Python: FastAPI, Pydantic, httpx, pytest (1000+ test suite experience).
• Production TypeScript/React: Next.js App Router, server components, Okta/NextAuth SSO, Playwright testing.
• AWS and Kubernetes: EKS operations, GitLab CI/CD, ArgoCD, Helm, Secrets Manager.
• Enterprise security patterns: Zscaler proxies, SSL certificates, Kubernetes networking, JWKS verification.
• Healthcare or regulated industry experience (HIPAA, SOC 2, or similar frameworks).
• Strong communication skills: run discovery sessions with non-technical stakeholders, explain security trade-offs to executives, and write architecture docs department leaders can follow.
• Servant leadership mindset: remove blockers for others, teach through questions not directives, and make stakeholders successful first.
• Thrives in organized chaos: 15 stakeholders, 6 systems, 3 sprints in flight.
• Bias toward shipping: “good enough to get feedback” beats “perfect in 3 months.”
• Highly collaborative: challenges ideas constructively and welcomes being challenged.
• Led small teams (2-5 people) through technical mentorship or tech lead roles.
• US-based (US Central time zone preferred; Poland also considered).
• Built agentic systems: agent coordination, scheduled routines, and feedback loops.
• MCP (Model Context Protocol) experience: custom connectors for enterprise systems.
• Active contributor to AI/ML communities (papers, open source, conference talks).
• Teaching through code: strong code review skills, pairing experience, and documentation focus.
• Experience teaching non-technical users through workshops, training sessions, and business-user documentation.

AI-Augmented Engineering (Non-Negotiable)

DrFirst runs on AI-assisted development. We use Claude (Anthropic) as our primary AI model via AWS Bedrock for enterprise control, and we are standardizing on AI coding assistants for all development work.

• Active, daily use of AI engineering tools (Claude Code, GitHub Copilot, Cursor, Windsurf, Cline, or similar). Hard requirement. You should be writing code with AI assistants, not just using them occasionally.
• Experience with Claude (Anthropic) is highly valued, whether through Claude.ai, Claude Code CLI, API integration, or AWS Bedrock. Our automation platform runs on Claude Sonnet 4.5.
• At least one automation you have built that eliminated hours of manual work, ideally using LLM APIs.
• Comfort teaching others to use AI tools effectively through pairing and code review.
• Primarily desk-based work, approximately 90-95% of the time, at a computer workstation.
• Occasional travel, less than 5-10% of the time.
• Backend: Python (FastAPI, Pydantic, httpx, pytest), OAuth2, AWS Secrets Manager, PostgreSQL, AWS Bedrock.
• Frontend: js 14 (React 18, TypeScript, Tailwind CSS), NextAuth.js/Okta SSO, Playwright.
• Infrastructure: AWS EKS (Kubernetes), GitLab CI/CD, ArgoCD, Helm, Zscaler proxies.
• AI and Agentic: Anthropic Claude (AWS Bedrock), AI coding assistants (GitHub Copilot/Cursor), MCP connectors.