AI Engineer Agentic & Generative AI Solutions

Role Overview

We are seeking an experienced AI Engineer to design and build production-grade Generative AI solutions with a strong focus on agentic workflows, multi-agent systems, and enterprise AI applications. The ideal candidate combines strong software engineering fundamentals with hands-on expertise in LLMs, RAG architectures, and AI agent frameworks.

Key Responsibilities

- Design, architect, and develop scalable Generative AI applications and agentic solutions for real-world business use cases.
- Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Microsoft Copilot Studio, or similar technologies.
- Develop and maintain backend services, APIs, microservices, and data pipelines that power AI-driven products.
- Implement advanced AI patterns including RAG, Agentic RAG, tool/function calling, planning & reflection loops, and human-in-the-loop workflows.
- Engineer and optimize prompts, system instructions, and agent workflows to improve reliability, accuracy, and user experience.
- Integrate LLMs with enterprise systems, third-party APIs, vector databases, and knowledge repositories.
- Monitor, evaluate, and continuously improve model and agent performance using observability tools, metrics, and user feedback.
- Collaborate closely with Product, Engineering, Data, and Design teams to deliver impactful AI solutions.
- Stay current with emerging AI technologies, frameworks, and best practices, contributing innovative ideas to the team.
- Document architectures, design decisions, and reusable solution patterns while supporting knowledge sharing across teams.

Required Qualifications

Must Have

- 515 years of overall software engineering experience.
- 1+ years of hands-on experience building applications using Generative AI and LLM technologies.




- Strong proficiency in Python and experience developing production-ready applications.
- Hands-on experience with at least two agentic AI frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility.
- Strong backend development skills, including REST/gRPC APIs, asynchronous programming, Docker, and frameworks such as FastAPI or Flask.
- Solid understanding of leading LLMs including OpenAI GPT models, Anthropic Claude, Google Gemini, and open-source alternatives.
- Practical experience building RAG solutions using vector databases such as Pinecone, Weaviate, ChromaDB, or Qdrant.
- Expertise in prompt engineering, LLM orchestration, structured outputs, guardrails, ReAct patterns, and evaluation techniques.
- Strong problem-solving, system design, and architectural decision-making skills.
- Excellent communication skills with the ability to collaborate effectively across global teams.

Preferred Qualifications

- Experience with AI observability and evaluation tools such as LangSmith, Ragas, DeepEval, Arize, or Weights & Biases.
- Familiarity with model adaptation and fine-tuning techniques (LoRA, PEFT, RLHF concepts).
- Experience with cloud AI platforms including Azure OpenAI, AWS Bedrock, or Google Vertex AI.
- Understanding of CI/CD, MLOps, and LLMOps practices.
- Exposure to graph databases, knowledge graphs, and structured data integration.
- Experience with event-driven architectures and messaging platforms such as Kafka or RabbitMQ.

What We're Looking For

- Engineers who build and deliver production-ready AI systems, not just prototypes.
- Professionals who can evaluate and recommend the right architecture, whether single-agent, multi-agent, RAG-based, or fine-tuned solutions.
- Solid ownership mindset with the ability to take AI solutions from concept through production deployment.
- Team players who contribute technical leadership, best practices, and continuous learning within a rapidly evolving AI landscape.

📌 Sr/Lead Gen AI Engineer (Hyderabad)
🏢 EPAM Systems
📍 Hyderabad