Principal AI Engineer
$175,000–$200,000 year
RemoteUnited States
Job Summary
Architect and build production AI automation systems from discovery to deployment, shipping 3-5 tools in parallel while debugging authentication flows and optimizing async performance. Lead department sprints for HR, Finance, Legal, and Marketing by mapping workflows with VPs, conducting discovery sessions, and teaching non-technical leaders to use AI tools effectively. Mentor 2-3 engineers through code reviews and pairing, removing blockers and translating technical security trade-offs for executives. Design multi-agent systems and enterprise integrations using Python/FastAPI, Next.js, and AWS Bedrock, ensuring HIPAA compliance and OAuth2 security across 15 stakeholders.
Required Qualifications
- 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
- 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
- US-based (US Central time zone preferred; Poland also considered)
Desired Qualifications
- Led small teams (2-5 people) through technical mentorship or tech lead roles
- 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
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