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