Senior Backend Developer - LLM Agent Platform

Location: Bangalore

Experience: 5+ years backend development, 12 years AI/LLM integration

About the Role

Were looking for an experienced AI Engineer to design and build production-grade LLM-powered systems . This role involves deep Python expertise, modern API development, and hands-on experience with agent orchestration frameworks like LangChain and LangGraph. Youll work on real-world AI workflows , integrating multiple LLM providers, optimizing pipelines, and ensuring enterprise-grade reliability.

Key Responsibilities

• Design & implement LLM workflows using LangChain/LangGraph (agents, tools, memory, orchestration).
• Build robust backend services with FastAPI (async execution, API gateways, OpenAPI docs).
• Develop prompting strategies , model evaluation pipelines , and orchestration logic for multi-provider LLM integration.
• Implement streaming endpoints , guardrails for safety (PII detection, prompt injection protection), and observability.
• Collaborate on architecture decisions , mentor team members, and maintain high code quality standards.

Required Skills

• Python (5+ years) : Production-level backend development, async patterns, type safety.
• AI/LLM Integration (12 years) : Prompt engineering, orchestration, pipeline design.
• LangChain & LangGraph : Agent workflows, graph-based orchestration, memory management.
• FastAPI : High-performance async APIs, OpenAPI documentation, API gateways.
• Strong understanding of RESTful API design , Docker , and CI/CD pipelines .
• Familiarity with testing strategies (unit/integration/E2E) and observability tools .

Preferred

• Experience with LangSmith , Guardrails AI , or similar debugging/safety frameworks.
• Knowledge of streaming protocols (SSE/WebSockets) and distributed systems concepts.
• Exposure to OpenTelemetry , structured logging, and performance optimization.

Why Join Us?

• Work on cutting-edge AI platforms with production-grade standards (not prototypes).
• Build systems that dynamically switch between multiple LLM providers.
• Collaborate in a documentation-driven, code-review culture focused on quality and scalability.

Tech Stack: Python, FastAPI, LangChain, LangGraph, Docker, CI/CD