Agentic AI/ML Engineer

Role & responsibilities

• Design, develop, and deploy Agentic AI applications using LLMs and AI agent frameworks.
• Build AI agents capable of reasoning, planning, decision-making, tool calling, and task execution.
• Develop multi-step AI workflows and agent-based automation solutions.
• Work with LLMs such as OpenAI, Azure OpenAI, Gemini, Claude, or open-source models.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise documents and knowledge bases.
• Integrate AI agents with REST APIs, databases, enterprise applications, and external tools.
• Develop and optimize prompts, system instructions, agent workflows, and tool/function calling.
• Build AI-powered web interfaces and dashboards using React.js / Angular / similar technologies.
• Work on UI/UX for AI applications including chat interfaces, agent dashboards, workflow visualization, and human-in-the-loop interactions.
• Evaluate AI responses for accuracy, reliability, latency, and cost.
• Implement appropriate guardrails, validation, logging, and monitoring for AI applications.
• Collaborate with software engineers, data engineers, and business teams to develop AI solutions.
• Create PoCs and convert successful prototypes into scalable enterprise applications.

Required Skills

• 13 years of experience in AI/ML, Generative/Agentic AI, Software Development, or related areas.
• Strong programming skills in Python.
• Hands-on understanding of LLMs and Generative/Agentic AI.
• Experience with AI Agents / Agentic AI workflows.
• Knowledge of RAG, embeddings, vector databases, and semantic search.
• Experience with REST APIs, JSON, API integration, and tool/function calling.
• Basic knowledge of React.js / Angular / JavaScript / TypeScript.
• Understanding of UI/UX principles and development of AI-powered interfaces.
• Knowledge of Git and software development practices.
• Good problem-solving and analytical skills.

Preferred candidate profile

• Experience with LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar agent frameworks.
• Experience with OpenAI API / Azure OpenAI / Gemini / Claude.
• Knowledge of vector databases such as Pinecone, FAISS, Chroma, Weaviate, or Milvus.
• Experience with MCP (Model Context Protocol) and AI tool integration.
• Understanding of AI memory, agent orchestration, multi-agent systems, and human-in-the-loop workflows.
• Exposure to AWS / Azure / GCP.
• Experience with Docker and basic CI/CD concepts.
• Familiarity with Figma or other UI/UX design tools is an advantage.