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
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
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
Our Interview Practices
Additional Information
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.