Senior Product Software Engineer (ML+ AI + Graph DB)
Skills
About the role
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
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
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
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
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. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you - not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
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