Description

Key Responsibilities

• Own component-level system design for modernization workstreams, documenting as-is processes and defining target architecture
• Design and build production-grade RESTful APIs and backend services in Python using FastAPI, Django, or Flask
• Implement GenAI capabilities including RAG and GraphRAG pipelines, LLM orchestration, prompt engineering, and semantic search
• Model and query domain knowledge using graph databases (Neo4j/Cypher) and vector databases (pgvector, Pinecone, Weaviate)
• Design relational schemas and optimize PostgreSQL for complex, performance-sensitive queries
• Build ETL/ELT pipelines to ingest, profile, and quality-assess legal and application data using AWS Glue
• Deploy and operate services on AWS using Docker, Kubernetes/EKS, with automated CI/CD pipelines

Qualifications

• 7-8 years of full-stack/backend software engineering experience with recent hands-on Generative AI delivery
• Strong proficiency in Python (FastAPI, Django, Flask) and RESTful API design
• Experience with LangChain, OpenAI API integration, prompt engineering, and embeddings
• Hands-on experience with PostgreSQL, Neo4j, and vector databases in production environments
• Proficiency with AWS services (EC2, S3, Lambda, Glue, EKS) and container orchestration (Docker, Kubernetes)
• Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions) and microservices architecture
• Strong understanding of component-level system design and distributed systems

Key Skills

Education

Bachelor's degree