About this role
The candidate will join a greenfield benefits administration platform to build and own three Python-based microservices focused on AI-driven and data-intensive capabilities. Responsibilities include developing a conversational AI assistant, a document management service, and a reporting engine using modern AWS technologies. The role involves building AI-powered features like intent classification, semantic search, and LLM integrations. The developer will work alongside a broader backend team that primarily uses Go, but will focus on areas where Python is most valuable. The technical environment includes FastAPI, PostgreSQL, AWS services, and microservice architecture.
Skills & technologies
Must have
- Python
- FastAPI
- Pydantic
- AWS
- boto3
- Amazon S3
- AWS Bedrock
- AWS Lambda
- EventBridge
- asyncio
- asyncpg
- SQLAlchemy
- PostgreSQL
- Docker
- pytest
- microservices
- event-driven design
Read full description
About The Role
In this role, you will join a greenfield benefits administration platform where you will build and own three Python-based microservices powering AI-driven and data-intensive capabilities. You will develop a conversational AI assistant, a document management service, and a reporting engine, leveraging modern AWS technologies and the Python ecosystem. While the broader backend team works primarily in Go, this role focuses on areas where Python delivers the greatest value through AI, vector search, document processing, and advanced data aggregation.
Responsibilities
In this role, you will join a greenfield benefits administration platform where you will build and own three Python-based microservices powering AI-driven and data-intensive capabilities. You will develop a conversational AI assistant, a document management service, and a reporting engine, leveraging modern AWS technologies and the Python ecosystem. While the broader backend team works primarily in Go, this role focuses on areas where Python delivers the greatest value through AI, vector search, document processing, and advanced data aggregation.
Responsibilities
- Design, develop, and maintain Python microservices that support conversational AI, document management, and reporting capabilities across the platform
- Own the delivery of scalable and reliable backend solutions, improving platform performance, data accessibility, and user experience
- Collaborate closely with backend engineers, product stakeholders, and cross-functional teams to ensure seamless integration through a shared API Gateway
- Build AI-powered features including intent classification, semantic search, multi-turn conversational workflows, and LLM integrations
- Develop document processing services supporting file storage, parsing, embeddings generation, indexing, and retrieval workflows
- Create reporting functionality that enables ad-hoc querying, scheduled execution, and export to formats such as CSV and PDF
- Optimize PostgreSQL data models, complex queries, and asynchronous database interactions to ensure efficient and secure processing
- Contribute to microservice architecture, event-driven designs, automated testing, CI/CD pipelines, and cloud-native deployment practices on AWS
- 3+ years of commercial experience with Python development in production environments
- Strong expertise in FastAPI, including async request handling, dependency injection, and Pydantic v2
- Hands-on experience with AWS services, including boto3, Amazon S3, and at least one of AWS Bedrock, Lambda, or EventBridge
- Solid knowledge of asynchronous Python development using asyncio, asyncpg, or SQLAlchemy async
- Proven experience working with PostgreSQL, including complex SQL queries and performance optimization
- Practical understanding of microservice architectures, distributed systems, and event-driven design patterns
- Experience with Docker, automated testing using pytest, and modern development workflows
- Familiarity with vector databases such as pgvector, Pinecone, Weaviate, or Qdrant (is an advantage)
- Experience with LLM technologies, AWS Bedrock, OpenAI, Anthropic Claude, LangChain, or LlamaIndex (is a plus)
- Knowledge of pandas, document parsing tools such as PyPDF or python-docx, and clean architecture principles (is beneficial)
- Capability to review and navigate Go code (an advantage)
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