We are looking for an AI Agentic Platform Engineer to build production-grade infrastructure for LLM-powered and multi-agent systems.

You will work across agent orchestration, LLM infrastructure, cloud-native platforms, distributed systems, evaluation, observability, and AI safety to build scalable platforms that support enterprise AI applications.

What You'll Do

- Build and maintain agentic AI platforms using LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks.
- Develop MCP integrations connecting AI agents with tools, APIs, and external systems.
- Design agent memory and retrieval systems using vector databases, semantic caching, and knowledge graphs.
- Build scalable cloud-native infrastructure using Kubernetes, Docker, Helm, and serverless technologies.
- Deploy and optimize LLM inference using vLLM, TensorRT-LLM, or Ollama, including GPU allocation and batching.
- Develop production platform services using Python, Go, or Rust.
- Implement AgentOps, evaluation, tracing, and observability using tools such as Ragas, DeepEval, LangSmith, Langfuse, Phoenix, or OpenTelemetry.
- Build secure execution environments using Firecracker, gVisor, WASM, or similar technologies.
- Implement AI guardrails, RBAC, audit logging, HITL controls, and safety mechanisms.
- Build model routing and fallback mechanisms for cost, latency, and performance optimization.
- Develop internal SDKs, APIs, CLI tools, templates, and platform utilities for AI application teams.





Required Qualifications

- 3+ years of backend, platform, cloud, MLOps, DevOps/SRE, or distributed-systems engineering experience.
- At least 1+ year of hands-on production experience building LLM-powered or agent-driven systems.
- Strong experience with platform engineering, MLOps/LLMOps, DevOps/SRE, or microservices architecture.
- Hands-on experience deploying and operating production AI/LLM systems on scalable cloud infrastructure.
- Robust programming experience in Python, Go, or Rust.
- Experience with Docker and Kubernetes in production environments.
- Strong understanding of distributed systems, APIs, networking, observability, and cloud infrastructure.
- Bachelor's or Master's degree in Computer Science, Software Engineering, AI, or a related technical field, or equivalent practical experience.
- Tier 1 / Tier 2 institute background preferred.

Preferred Technical Experience

Agentic AI:

LangGraph, LangChain, CrewAI, AutoGen, MCP

Infrastructure:

Kubernetes, Docker, Helm, Serverless, AWS/Azure/GCP

LLM Serving:

vLLM, TensorRT-LLM, Ollama, GPU infrastructure

Programming:

Python, Go, Rust

Memory & Retrieval:

Pinecone, pgvector, Redis, Vector DBs, Knowledge Graphs, Semantic Caching

Evaluation & Observability:

Ragas, DeepEval, LangSmith, Langfuse, Phoenix, OpenTelemetry, Braintrust

Security & Safety:

Firecracker, gVisor, WASM, NeMo Guardrails, Guardrails AI, RBAC, HITL

📌 AI Agentic Platform Engineer (Chennai)
🏢 N2P Systems
📍 Chennai