AI / Generative AI Engineer – Python, LLMs, RAG, AI Agents, Azure OpenAI & AWS Bedrock

Job Summary Synechron is seeking an AI / Generative AI Engineer with 6+ years of experience in designing, developing and deploying AI-powered applications. The role will focus on Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), cloud-based AI platforms and production-grade software engineering. The position will work with business stakeholders, solution architects, engineering teams, DevOps and MLOps teams to deliver scalable AI solutions that address business needs, integrate with enterprise applications and operate reliably in production environments. This is a full-time position based in Pune, Bengaluru, Hyderabad or Mumbai, with a hybrid working model. The role contributes to business objectives by accelerating AI adoption, improving automation, enabling intelligent applications and delivering secure, maintainable and measurable AI capabilities. Software Requirements Required Python: Strong hands-on experience in Python development for AI applications, data processing, model integration and API development; experience with the project-supported version. Generative AI and LLMs: Practical experience developing applications using LLMs and foundation models. NLP and Transformers: Working knowledge of Natural Language Processing, Transformers, embeddings and prompt engineering. RAG: Experience designing and implementing Retrieval-Augmented Generation pipelines. Vector Databases: Experience with one or more of the following:PineconeChromaDBFAISSWeaviateEquivalent vector database technologies LangChain and LangGraph: Hands-on experience building LLM applications, orchestration workflows or AI agents using current project-supported versions. Agentic AI Frameworks: Experience developing intelligent AI agents and agentic workflows. Model Context Protocol (MCP): Working knowledge or practical experience applying MCP concepts in AI applications. OpenAI / Azure OpenAI: Experience integrating and using OpenAI or Azure OpenAI services. AWS Bedrock: Experience using AWS Bedrock or equivalent managed foundation-model services. Hugging Face Ecosystem: Familiarity with relevant models, libraries and tools used for Generative AI development. Cloud Platforms: Hands-on experience with Azure and/or AWS. REST APIs and FastAPI: Experience designing or integrating REST APIs and developing AI services using FastAPI. Docker and Kubernetes: Experience containerizing and deploying AI applications and services. CI/CD Pipelines: Experience supporting automated build, test and deployment pipelines. Git and GitHub/GitLab: Experience with source control, branching, code review and collaborative development. SQL and NoSQL Databases: Experience working with structured and unstructured data stores. Data Pipelines: Experience with data ingestion, preparation and processing pipelines. MLOps: Experience with model deployment, monitoring and machine learning lifecycle management.