Senior Backend Developer, AI Pods

We are seeking a Senior Backend Developer to join our AI Pods team, building robust AI-powered API services and agentic workflows. This role focuses on language model interaction with internal systems, vector databases, and external tools via orchestration frameworks, treating LLMs as components in a secure, scalable distributed system. Responsibilities Design and build backend API services and LLM orchestration layers Own API contracts and service reliability end-to-end, ensuring AI edge cases fail gracefully Integrate LLMs using rigorous systems engineering, bake in evaluation, observability, fallback handling, and cost awareness Implement and maintain complex RAG pipelines, including document ingestion, chunking, embedding, and retrieval optimization Develop and connect agent tools using LangChain, LangGraph, and potentially MCP (Model Context Protocol) Build reliable, reusable orchestration frameworks and logic for downstream developer consumption Ensure security, privacy, enterprise-grade observability, and test coverage across all backend workflows Contribute to architecture decisions and engineering standards within the pod Collaborate with frontend engineers, data engineers, and infrastructure teams Requirements 3+ years of backend engineering experience, focused on microservices and distributed systems Proficiency in Python for high-performance backend services and cloud-native APIs Familiarity with AWS, Docker, and ECS/EKS Knowledge of RESTful APIs Understanding of secure coding practices and strong auth/authz fundamentals English proficiency at B2 level or higher Nice to have 1+ years of hands-on experience with AI SDKs (OpenAI, Anthropic/Claude, AWS Bedrock, or equivalent) in production Practical experience with vector databases (Amazon Kendra, OpenSearch), embedding strategies, and retrieval systems Hands-on experience with LangChain, LlamaIndex, or LangGraph Familiarity with AI evaluation tooling or real-time APM (LangSmith, Langfuse, Arize) Skills in React and TypeScript Experience deploying to EKS environments at scale Understanding of agent interoperability patterns (MCP) Knowledge of identity/security domain (IAM, CIAM) Flexibility to use secondary languages such as Java, Node.js, or Go