Principal AI Engineer

We’re looking for a hands-on, visionary builder to lead the end-to-end development of
a free, modern ATS (Applicant Tracking System) built for both external clients and
internal ops. As the founding engineer, you’ll architect clean, cloud-agnostic, scalable systems while
using AI agents as true leverage to accelerate development. This role is ideal for someone who
thrives on rapid iteration, treats AI as a productivity multiplier, and is ready to ship fast, safe, and
measurable results.

Qualifications:

• 5+ years of solid programming experience as a Full-Stack Engineer using Python.**
• Experience with Postgres, Redis (jobs/cache), and OpenAPI.
• 2+ years building B2B SaaS products, contributing across backend and frontend.**
• Strong skills in TypeScript, Node.js, and SQL schema design, with exposure to performance optimization.**
• Frontend: 2+ years using React or Next.js, including component libraries and form/runtime validation.**
• Experience with Visual Studio
• Infrastructure: Comfortable with Docker, IaC-friendly setups, and cloud environments (AWS, GCP, Azure).
• AI-assisted development: 1+ year of hands-on experience using Cursor or Copilot as part of daily development workflow.**
• Exposure to AI-native engineering concepts: prompt design, tool calling, or agent orchestration.**
• Proven record of delivering solo projects or end-to-end features independently (at least 3).
• Pragmatic product mindset: able to collaborate on crisp tickets, contribute to acceptance criteria, and make thoughtful trade-offs that protect UX and delivery speed.
• Experience working in small, fast-paced teams (“build-everything” mentality): hands-on, resourceful, and adaptable.**

Desired Skills:

• ATS/HRIS/CRM domain, multi-tenant theming/white-label, public APIs/webhooks, SOC 2 readiness, EN/ES.

Responsibilities:

• Architecture (cloud-agnostic): Design a modular, multi-tenant Node.js/Typescript and Python + Postgres platform; containerize with Docker; keep providers swappable (object storage, email, queues).
• Full-stack delivery: Stand up core ATS flows (req intake, pipeline/Kanban, scheduling, scorecards, hosted careers) and initial CB Ops modules.
• AI as workforce: Build and operate an in-house agent framework (tool registry, retries/backoff, state store, H/ITL gates, evals). Treat agents like junior developers: task, test, and monitor cost/latency.
• LLM-agnostic integration: Abstract providers behind a simple interface; support fallbacks, timeouts, and circuit breakers; add offline mocks for tests.
• Quality & safety: Implement RBAC, audit logs, PII handling, prompt-injection defenses, bias guardrails, and deterministic transforms where needed.
• Operability: CI/CD, feature flags, migrations, OpenTelemetry traces, structured logs, metrics for WAUs, submit? interview time, PQL triggers.

**MUST HAVE SKILLS