Senior Agentic AI Engineer

• 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
• Originally posted on Himalayas