Description

You design, develop, and operate scalable microservices powering the runtime and serving layer for AI/ML agents and RAG components, focusing on reliability and performance.

Responsibilities

• Implement and maintain LLM orchestration frameworks and integrate them with core applications to enable agent workflows.
• Build and optimize secure data ingestion and indexing pipelines for RAG using vector and graph databases.
• Develop secure, scalable data connectors and tool interfaces for enterprise systems like Oracle, Salesforce, Workday, and Snowflake.
• Design and implement automated evaluation frameworks to measure LLM performance and integrate them into CI/CD pipelines.
• Collaborate with Security teams to embed access controls, auditability, and privacy into AI/ML services.

Required Skills

• 5+ years of professional software engineering experience building backend services or internal platforms in a cloud-native environment.
• Strong programming skills in Python and/or TypeScript/Node.js for backend services supporting AI/ML workloads.
• 2+ years of hands-on experience deploying solutions using Generative AI/LLM technologies.
• Practical experience with LLM orchestration and RAG/agent frameworks (e.g., LangChain, LangGraph).
• Hands-on work with vector databases and graph databases like Neo4j, including query optimization.
• Experience integrating LLM applications with complex enterprise data sources such as Oracle, Salesforce, Workday, and Snowflake.
• Solid understanding of AWS services, including Docker, Kubernetes, and CI/CD practices for AI/ML services.

Key Skills

Education

Bachelor's degree