We are seeking a Senior Backend Developer to integrate our AI Pods team and engineer trustworthy AI-driven API services together with agentic workflows. The role centers around empowering language models to communicate with internal systems, vector databases and external tools via orchestration frameworks. You will handle LLMs as modular pieces inside a secure, scalable distributed setting, owning API contracts and service uptime while embedding LLMs through rigorous systems engineering practices covering evaluation, observability, fallback handling and cost awareness.

Responsibilities

• Design and implement backend API services together with LLM orchestration layers
• Construct and maintain advanced RAG pipelines spanning document ingestion, chunking, embedding and retrieval optimization
• Develop and integrate agent tools through LangChain, LangGraph and possibly MCP (Model Context Protocol)
• Safeguard security, privacy, enterprise-grade observability and test coverage across every backend workflow
• Drive architecture decisions and engineering standards within the pod
• Collaborate with frontend engineers, data engineers and infrastructure teams
• Own API contracts and service reliability, securing graceful failure of AI edge cases
• Provide robust, reusable orchestration frameworks and logic meant for downstream developer consumption

Requirements

• 3+ years of backend engineering experience focused on microservices and distributed systems
• 2+ years working with Python on high-performance backend services and cloud-native APIs
• Expertise in AWS, Docker and ECS/EKS
• Background in RESTful API development
• Knowledge of secure coding practices paired with strong auth/authz fundamentals
• Upper-Intermediate English language proficiency (B2)

Nice to have

• 1–2+ years of real-world production work with AI SDKs such as OpenAI, Anthropic/Claude or AWS Bedrock
• Familiarity with vector stores (Amazon Kendra, OpenSearch) coupled with embedding strategies and retrieval systems
• Direct involvement with agentic frameworks like LlamaIndex
• Skills in AI evaluation tooling or real-time APM platforms (LangSmith, Langfuse, Arize)
• 1–2+ years devoted to React and TypeScript, combined with large-scale EKS deployments
• Understanding of agent interoperability patterns (MCP), identity/security areas (IAM, CIAM) and extra languages such as Java, Node.js or Go