Agentic AI - Pan India
Price Waterhouse Coopers · Kolkata · hybrid · Posted 45d ago
Undisclosed4–6 yrsfulltimeSourced from
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About this role
Role : Gen-AI / Agentic AI Automation Engineer
Location : Pune , Kolkata , Bangalore
Eligibility:
- Education: B.Tech/B.E./M.Tech in in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.
- Work Experience: 4-6 years of hands-on experience in software development, with at least 2-3 years focused on Agentic AI or GenAI technologies.
- Experience in Hands-on code development using GenAI / Agentic AI tools to design, build, and deploy enterprise-grade AI solutions powered by one or more of the following LLMs like GPT-4, Anthropic Claude, Mistral, using Google Vertex AI/Deep Mind, Azure OpenAI, AWS Bedrock, Azure AI Foundry, etc.
- Must have strong understanding of Retrieval-Augmented Generation (RAG), Embeddings, Prompt Engineering, Semantic Search, Vector Databases.
- Must have strong Python development expertise and practical experience implementing GenAI applications, agent orchestration frameworks like LangGraph, LangChain, AutoGen,CrewAI, etc, vector search technologies, and cloud-native AI solutions using OpenSearch, Pinecone, Chroma, Azure AI Search, pgvector, etc
- Must have in-depth understanding of Datawarehousing and datalake concepts and experience in developing autonomous ETL/Pipeline and orchestration of backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices.
- Experience working with structured and unstructured data sources, including documents, PDFs, APIs, databases, and knowledge repositories. Exposure to Agile development processes.
- Implement and optimize prompt engineering techniques to enhance AI model performance.
- Working knowledge of cloud environments such as AWS, Azure, or Google Cloud.
- Write clean, maintainable, and efficient code adhering to coding standards.
- Support debugging, performance tuning, and deployment of GenAI solutions in cloud environments.
- Stay updated with the latest advancements in GenAI and contribute to continuous improvement.
- Knowledge of Docker, Kubernetes, CI/CD, and software engineering best practices.
- Certification in Python, AI/ML, or cloud technologies like Azure AI, Deeplearning.AI is good to have.
Mandatory Skills: Python, SQL, Data Engineering (ADF , Databricks), Generative AI Copilot, LangGraph / CrewAI / and MCP
Key Responsibilities:
- Design and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures.
- Build and orchestrate multi-agent workflows, including planner, retriever, executor, validator, and human-in-the-loop patterns.
- Develop backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices.
- Design and implement document ingestion, embedding generation, vector indexing, reranking, and retrieval pipelines.
- Integrate AI applications with enterprise systems, APIs, databases, document repositories, and cloud services.
- Deploy, monitor, and support GenAI applications using Docker, Kubernetes, CI/CD pipelines, and cloud platforms.
- Implement LLMOps best practices, including model evaluation, prompt management, monitoring, logging, observability, and cost optimization.
- Collaborate with business and technology stakeholders to deliver scalable AI solutions that generate measurable business outcomes.
Sourced from naukri
Skills
cloud platformAgentic AiGenerative Ai
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Price Waterhouse Coopers
Management Consulting
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