Role Summary
We are seeking an experienced Azure AI/ML Engineer with strong expertise in Generative AI, Agentic AI, LLMs, RAG, and Multi-Agent Systems. The ideal candidate will be responsible for designing, developing, deploying, and supporting production-grade AI solutions using Azure AI services, modern orchestration frameworks, and enterprise AI engineering practices.
This role requires hands-on experience building intelligent agents, agent orchestration frameworks, retrieval-augmented generation (RAG) solutions, observability frameworks, and scalable AI applications in cloud environments.
Key Responsibilities
- Design, build, and deploy Agentic AI and Generative AI solutions using Azure AI technologies.
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases.
- Build and manage multi-agent architectures, orchestration workflows, and agent collaboration patterns.
- Implement prompt engineering, tool calling, MCP integrations, and agent-to-agent (A2A) communication.
- Design retrieval, chunking, embedding, reranking, and grounding strategies for LLM applications.
- Deploy and maintain AI solutions in production environments with monitoring, telemetry, and observability capabilities.
- Evaluate model performance using quantitative and qualitative metrics.
- Collaborate with architects, product teams, and business stakeholders to deliver AI-powered solutions.
Required Technical Skills
Generative AI & LLMs
- Strong hands-on experience with:
- Azure OpenAI Service
- Large Language Models (LLMs)
- Prompt Engineering
- Function Calling / Tool Calling
- AI Agent Development
Agentic AI
- Experience designing and implementing:
- Multi-Agent Systems
- Agent Orchestration
- Agent Routing & Intent Classification
- Agent-to-Agent (A2A) Communication
- Model Context Protocol (MCP)
- Agent Skills and Tool Integrations
RAG & Knowledge Retrieval
- Strong understanding of:
- RAG Architecture
- Chunking Strategies (Recursive, Semantic, Fixed Size)
- Embeddings & Vector Search
- Retrieval and Re-ranking
- Grounded Responses
- Knowledge Base Integration
AI Frameworks
Hands-on experience with one or more:
- LangChain
- LangGraph
- Semantic Kernel
- AutoGen
- CrewAI
- DeepAgents
- MCP Frameworks
AI Evaluation & Monitoring
Experience with:
- Context Precision & Recall
- Groundedness
- Correctness & Completeness Metrics
- Response Quality Evaluation
- Telemetry & Observability
- Production Monitoring and Alerting
Programming & Cloud
- Advanced Python development skills.
- REST APIs and backend development.
- Experience with Azure cloud services and AI workloads.
- CI/CD, GitHub, GitHub Copilot, DevOps practices.
Preferred Skills
- Azure AI Foundry
- Azure AI Search
- Azure Machine Learning
- Vector Databases
- Knowledge Graphs (Neo4j)
- Conversational AI and Voice Agents
- MLOps and Model Lifecycle Management
Experience
- 8+ years of software engineering, AI/ML, or data engineering experience.
- 4+ years of hands-on experience building GenAI, Agentic AI, or RAG-based solutions.
- Experience deploying and supporting production AI applications.
Ideal Candidate Profile
Candidates should demonstrate strong practical expertise in:
- Building Agentic AI solutions and Multi-Agent Architectures
- Designing and optimizing RAG pipelines
- Agent orchestration, routing, and workflow design
- MCP and tool integration patterns
- LLM evaluation, benchmarking, and monitoring
- Production support, observability, and operational excellence
- Architecture design and technical decision-making
- Hands-on individual contributor development experience
Preferred Domain Experience: Enterprise AI Assistants, Conversational AI, Intelligent Automation, Knowledge Management, Customer Service AI, or Digital Transformation initiatives.