Senior Product Software Engineer (ML+ AI + Graph DB) (Pune)

Position Summary We are seeking a highly skilled Senior AI / Full Stack Engineer with deep expertise in modern AI systems and strong hands-on experience in full-stack development. This role focuses on building AI-powered and agentic applications, leveraging LLMs, autonomous agents, and intelligent workflows. You will design and develop systems that incorporate advanced LLM techniques , Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and agent-based architectures, enabling intelligent automation and decision-making across applications. Education Bachelor s degree in Engineering, Computer Science, or equivalent. Must Have : - 9+ years of professional software development experience, 3 years of relative experience in building AI product AI / LLM Agentic Systems - Strong understanding of AI/ML concepts with hands-on AI application development - Experience working with Large Language Models (LLMs) (Azure OpenAI, OpenAI, Claude APIetc.) LLM RAG Foundations - Deep knowledge of: - Prompt engineering optimization - Retrieval-Augmented Generation (RAG) - Embeddings and vector databases (Azure AI Search, Pinecone, FAISS, etc.) - Tokenization, context handling, hallucination mitigation Agentic AI MCP Expertise - Strong understanding of agent-based architectures (single-agent multi-agent systems) - Experience designing and building autonomous or semi-autonomous AI agents Agent Frameworks - Hands-on experience with frameworks such as: - Semantic Kernel (preferred for .NET ecosystem) - LangChain / LangGraph - LlamaIndex / AutoGen (or similar) Agent Capabilities - Experience implementing: - Tool-using agents (function calling, API integrations) - Planning and reasoning workflows (ReAct or similar patterns) - Agent orchestration and workflow automation - Building or integrating MCP-compatible servers/tools - Understanding of: - Memory models (short-term, long-term, vector memory) - Human-in-the-loop systems - AI guardrails, safety, and observability Core Engineering Skills - Solid knowledge of multi-threading, scalability, performance, and security - Experience with relational databases (SQL Server, PostgreSQL) - Experience with cloud platforms (Azure preferred) - Knowledge of Azure AI ecosystem (Azure OpenAI, Cognitive Services, AI Search) - Experience working in Agile/Scrum environments - Strong debugging, problem-solving, and analytical skills - Experience with Git and version control systems - Experience with Python for AI/ML pipelines - Exposure to Graph-based systems / Knowledge Graphs (Neo4j, Cosmos DB, etc.) - Experience with model evaluation, monitoring, and prompt/agent testing frameworks - semantic search - Machine Learning: Recommendation engines, demand forecasting, anomaly detection, clustering, predictive modelling, deep learning, graph-based scoring community analysis - Use of Copilot tools like Codex, Claude, GHCP etc. for software development. - Have developed software using SDD with help of SpecKit, OpenSpec etc. Nice to Have - Experience with fine-tuning or custom LLM pipelines - Experience with multi-agent orchestration frameworks (CrewAI, advanced AutoGen use cases) - Frontend experience with ReactJS, JavaScript, HTML5, CSS3 - Knowledge of CI/CD and MLOps practices - Exposure to multi-modal AI systems - Familiarity with MCP ecosystems, tool registries, or emerging AI interoperability standards - Experience in C#, .NET Core/.NET Framework - Experience with RESTful APIs and distributed systems Essential Duties and Responsibilities - Design and develop AI-first and agentic applications using LLMs and modern frameworks - Build and optimize RAG pipelines, embeddings, and semantic search systems - Design and implement autonomous agents and multi-agent workflows - Develop and integrate MCP-based tools and services to enable AI interaction with enterprise systems - Integrate AI capabilities into enterprise applications and backend systems - Collaborate with architects to build scalable AI-enabled cloud architectures - Ensure performance, reliability, safety, and observability of AI systems - Guide and mentor developers in AI engineering and agentic design patterns - Work closely with product, design, and data teams to deliver AI-driven features - Troubleshoot and resolve complex issues across AI and traditional systems - Maintain clean, testable, and well-documented code - Stay updated with latest advancements in LLMs, agentic AI, MCP, and AI tooling ecosystem What We re Looking For - Engineer who can build production-grade AI systems, not just prototypes - Robust understanding of LLMs, agents, and tool integration protocols (like MCP) - Ability to design end-to-end intelligent workflows and automation systems - Balance of software engineering excellence + AI innovation mindset Our Interview Practices To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts .