Lead Product Software Engineer (Microsoft Tech Stack)

Position Summary 

We are seeking a highly skilled Lead Product Software Engineer (AI/ML) with deep expertise in modern AI/ML systems. This role focuses on building AI/ML 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 :  

• 11+ years of professional software development experience, 8+ 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 

• Strong 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 

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/ML systems, not just prototypes  

• Strong 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