Senior Agentic AI Engineer

Job Description This is a remote position. Senior AI & Agentic System Engineer Experience: 5+ Years Location: Gurgaon, India / Fully Remote Team: AI Platform / Engineering About the Role We are looking for a Senior AI & Agentic System Engineer to design and build production-grade AI agents that can reason, use tools, interact with APIs, and execute complex multi-step workflows. You’ll work at the intersection of LLM engineering, agent architecture, backend systems, and cloud infrastructure , with significant ownership over architecture, reliability, evaluation, and scalability. Requirements Key Responsibilities Design and build autonomous AI agents capable of tool use, web/API interaction, memory, and multi-step task execution. Architect agentic workflows including planner/executor/verifier, multi-agent, HITL, retry, and failure-recovery patterns . Integrate LLM providers such as OpenAI, Anthropic, and Gemini , including structured outputs, function calling, context management, and prompt optimization. Build RAG and knowledge pipelines using embeddings, vector databases, hybrid search, reranking, and agent memory. Develop scalable backend services using Python and/or Node.js/TypeScript , REST/GraphQL APIs, async processing, and background jobs. Design reliable distributed systems with appropriate patterns for state persistence, caching, idempotency, event-driven workflows, and fault tolerance. Build observability and evaluation frameworks for AI systems, including tracing, behavioral regression testing, latency, quality, and token-cost monitoring. Own CI/CD and cloud deployments across development, staging, and production environments. Evaluate emerging technologies such as MCP, A2A, reasoning models, and agent frameworks and recommend practical adoption. Required Skills 5+ years of software/backend engineering experience with strong system-design expertise. Hands-on experience building production AI agents , beyond basic chatbot implementations. Strong experience with at least one major LLM provider SDK: OpenAI, Anthropic, or Gemini . Strong understanding of prompt engineering, tool/function calling, structured outputs, context management, and token optimization . Experience with agent frameworks/patterns such as LangGraph, CrewAI, AutoGen, ReAct, or plan-and-execute . Strong Python and/or Node.js/TypeScript development skills. Experience with RAG, embeddings, vector databases, hybrid retrieval, and reranking . Strong knowledge of REST/GraphQL APIs, asynchronous processing, databases, and distributed systems . Hands-on AWS experience, particularly Lambda, ECS/Fargate, API Gateway, S3, SQS, SNS/EventBridge, IAM, and CloudWatch . Experience with Docker, GitHub Actions, and Terraform . Understanding of AI security, including prompt injection, guardrails, output validation, and safe tool execution . AI/LLMOps & Evaluation Experience with tools such as: Langfuse, LangSmith, Helicone, or Arize Phoenix RAGAS, DeepEval, Promptfoo, or Braintrust LLM tracing, behavioral evaluations, regression testing, and cost monitoring. Nice to Have Browser automation using Playwright or Puppeteer . Experience with multimodal/vision-based agents. Knowledge of GraphRAG and knowledge graphs . Experience with Temporal or durable workflow execution . Open-source contributions to AI tooling. Background in ML/data science alongside software engineering. Tech Stack LLMs: OpenAI, Anthropic Claude Agent Infrastructure: Custom orchestration, MCP Backend: Python, Node.js/TypeScript Cloud: AWS Lambda, ECS/Fargate Data: PostgreSQL, S3, SQS, DynamoDB CI/CD: GitHub Actions Observability: Datadog, CloudWatch, Langfuse IaC: Terraform Browser Automation: Playwright