Years of experience: 6- 12 years
Locations: Bangalore, Noida, Indore
Job Description
- 6-10 years of software engineering experience, with at least 2+ years building production AI/ML or LLM-powered applications.
- Deep expertise in LangChain and LangGraph (you have built non-trivial multi-agent systems with cycles, persistence, and streaming).
- Strong experience with MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication standards.
- Expert-level Python, FastAPI, async programming, WebSockets, and building scalable APIs.
- Proven track record designing and shipping microservices or large-scale enterprise applications.
- Hands-on experience deploying containerized workloads on GKE (or equivalent like EKS/AKS) Helm, Kustomize, GitOps (ArgoCD/Flux), IAM, networking.
- Solid understanding of LLM evaluation, prompt engineering, retrieval-augmented generation (RAG), and agent reliability techniques.
- Experience with observability in AI systems (LangSmith, Phoenix, Helicone, or custom tracing).
- Strong grasp of software engineering fundamentals: testing (pytest, integration tests for agents), CI/CD pipelines, design patterns, Code reviews etc.
- Experience working on Agile delivery methodology.
Roles & Responsibilities
- Design and build reusable Agentic AI framework and workflows on top of LangChain/LangGraph (VertexAI or Bedrock)
- Lead integration of agents with external tools/APIs via Model Context Protocol (MCP), Agent-to-Agent (A2A) protocol, function calling, and custom connectors.
- Build high-performance backend services using FastAPI, async Python, Pydantic, and event-driven patterns.
- Design systems following microservices and enterprise application design principles.
- Ensure automated CI/CD pipelines and production deployment on Google Kubernetes Engine (GKE), including autoscaling, observability (Prometheus/Grafana, OpenTelemetry), and resilience patterns.
- Awareness of using LangSmith, LangFlow or similar such frameworks
- Establish engineering best practices for agent development (testing agents, version control of prompts/tools, rollback strategies, guardrails).
- Collaborate with product, data science, and platform teams to productionize agents that solve real enterprise problems.
- Expertise in writing clear and concise prompts with different tuning mechanism
- Expertise in implementing RAG based solution/agents leveraging knowledge base creation using vector databases.
- Mentor junior engineers and conduct architecture & code reviews.
- Well equipped in using Code assist tools like copilot, cursor, windsurf or other equivalents.
