Description

Build and scale async APIs and multi-agent AI workflows using Python and FastAPI.

This role is remote.

Responsibilities

• Design and maintain async REST/WebSocket APIs with Python 3.11+, FastAPI, and clean vertical-slice architecture.
• Implement multi-agent workflows using Semantic Kernel to route traffic among specialized LLM agents.
• Integrate LLM providers (OpenAI, Gemini) behind a provider-agnostic layer for cost-aware routing.
• Deliver Retrieval-Augmented Generation (RAG) using vector stores like Azure AI Search, pgvector, or Chroma.
• Maintain CI/CD pipelines with Bitbucket Jenkins, ensuring linting, testing, Docker packaging, and deployment.

Required Skills

• 5+ years building production APIs in Python; 2+ years with FastAPI.
• Deep knowledge of async I/O, Pydantic v2, dependency injection, and observability.
• Hands-on experience with Semantic Kernel or comparable agent frameworks.
• Practical implementation of RAG using Azure AI Search, pgvector, or Chroma.
• Strong Postgres skills with SQLModel/SQLAlchemy 2 and Alembic migrations.
• Proven integrations with LLM APIs (OpenAI, Gemini) and structured-output design.
• Dependency management via Poetry and virtual-env isolation.
• End-to-end CI/CD ownership from build to deploy.

Preferred Skills

• Experience with event/message queues (RabbitMQ, Azure Service Bus, Kafka).
• Familiarity with observability stacks like Grafana or LangFuse for LLM cost governance.

Key Skills

Education

Any Graduate