We are hiring a
Lead Python Developer with React
to spearhead the build-out of an enterprise-grade agentic AI platform powered by Python and AWS. The platform coordinates AI agents to automate complex professional workflows. In this role, you will shape architectural direction, lead a team of engineers and safeguard production reliability across a multi-environment deployment pipeline. This hands-on leadership position blends deep backend engineering with modern AI/LLM integration know-how.
Lead end-to-end delivery of an enterprise-grade agentic AI platform Shape architectural direction and evolve the design of distributed systems Coordinate AI agents to automate complex professional workflows Safeguard production reliability across CI/INT/QA/PROD environments Provide technical leadership and mentorship to a team of engineers Run code reviews and oversee technical debt management Evaluate architectural trade-offs to balance business and engineering priorities Embed large language models into applications through prompt engineering and agent delegation patterns Programmatically provision and govern cloud infrastructure across multiple accounts and environments Establish and refine CI/CD pipelines along with automated deployment workflows 5+ years of hands-on backend engineering experience with deep proficiency in Python (3.11+), covering async/await patterns and Pydantic data modeling Showcase of modular package design within a mono repo leveraging uv workspaces Expertise in FastAPI for delivering production REST APIs with dependency injection, middleware and SSE streaming Practical background in LLM / AI Agent Engineering, ideally with Anthropic Claude, spanning tool/skill orchestration and agent delegation Solid command of AWS Cloud Services including EKS (Kubernetes), RDS (PostgreSQL) and S3, complemented by Redis, ECR and Cognito Familiarity with AWS Bedrock and AgentCore for managed LLM hosting and serverless agent runtime environments Qualifications in AWS CDK for Infrastructure as Code spanning multiple accounts and environments Strong grasp of SQL and the data layer through SQLAlchemy (async), Alembic migrations and PostgreSQL Competency in CI/CD workflows using GitHub Actions and Docker (multi-stage builds) Demonstrated technical leadership in coaching engineers and steering architectural decisions English proficiency at B2 level or higher Flexibility to use React 18, Zustand and TanStack Query, paired with Vite for crafting modern TypeScript-based frontends Skills in testing approaches with pytest (async, parallel), Playwright for E2E coverage and quality gate enforcement in CI pipelines Knowledge of LLM observability platforms such as Langfuse or Promptfoo for tracing, evaluating and monitoring LLM behavior Capability to implement distributed tracing and application monitoring with OpenTelemetry and Datadog Background in security and compliance tooling such as SonarQube or Snyk, together with Artillery for load and performance testing Proficiency in Jinja2 prompt templating for maintainable, template-driven prompt systems
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