AI Engineer
work and our federal modernization programs. This is a hands-on builder role on a small, senior team. Engineers
own work end-to-end including data, model integration, services, UI, infrastructure, security, and deployment. You will be expected to make sound technical calls under federal compliance, security, and procurement constraints. Requirements:
- Education: Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Computational Linguistics, or a related field; Master’s is a bonus.
- Experience: 1-3 years of professional experience building and shipping ML or NLP systems, including focus on LLM based or Generative AI solutions.
- Strong production experience in Python and TypeScript, with modern web frameworks on both sides (e.g. FastAPI, React).
- Hands-on integration of LLMs into real applications — streaming, tool / function calling, token accounting, and failure handling — across at least one of OpenAI, Anthropic, Bedrock, Vertex, or Azure OpenAI.
- Experience designing agentic systems: multi-step workflows, retrieval-augmented generation, evaluation, and human-in-the-loop guardrails.
- Solid relational data modeling on PostgreSQL with an async ORM and migration tooling.
- AWS fluency (compute, storage, IAM, secrets, networking, observability) and infrastructure-as-code, ideallyTerraform.
- Practical understanding of OAuth / OIDC, JWT, RBAC, multi-tenant isolation, and least-privilege design.
- Disciplined testing, linting, and type-checking habits; reviewable diffs and clear written communication.
- Federal program exposure: NIST 800-53, FedRAMP, FISMA, ATO process, or agency-specific data-handling requirements.
- Experience with Keycloak or another OIDC provider, RLS-based multi-tenancy, or zero-trust application design.
- Working knowledge of a data/lakehouse platform (Databricks, Snowflake) and SQL beyond CRUD.
- Document AI / OCR pipelines and modernization of legacy enterprise workflows.
- Production observability (CloudWatch, OpenTelemetry, Grafana) and incident-response experience.
- Supply-chain hardening: SBOMs, dependenc y scanning, signed builds, threat modeling.
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