AI/ML Engineer

About the Role

We are looking for a AI/ML Engineer with deep, hands-on expertise in designing, building, and deploying production-grade GenerativeAI, RAG, and Agentic AI solutions on the Azure cloud platform. This is a full-stack AI engineering role spanning model development, orchestration, deployment, and operations — ideal for someone who thrives at the intersection of applied machine learning, LLM engineering, and scalable cloud architecture.

You will work on high-impact AI initiatives, building intelligent systems that combine LLMs, retrieval pipelines, and autonomous agents into robust, enterprise-ready applications.

Key Responsibilities

• Design, develop, and deploy end-to-end GenAI, RAG, and Agentic AI solutions using Azure OpenAI Service and the broader Azure AI ecosystem.
• Build and optimize LLM orchestration pipelines, prompt engineering strategies, and AI evaluation frameworks to ensure quality, reliability, and performance.
• Architect and implement vector search and retrieval systems using Azure AI Search, Pinecone, Chroma, Weaviate, or similar technologies.
• Develop scalable, production-grade data pipelines using Python and PySpark, including feature engineering and distributed data processing.
• Build, train, and optimize Machine Learning, Deep Learning, and NLP models, and manage their lifecycle using Azure Machine Learning.
• Own API development and model deployment, applying MLOps best practices including CI/CD, monitoring, and observability.
• Implement Responsible AI, AI Governance, and explainability practices to ensure ethical, transparent, and compliant AI systems.
• Collaborate with cross-functional teams (data engineering, product, and business stakeholders) to translate requirements into scalable AI solutions.
• Stay current with emerging GenAI/Agentic AI frameworks and evaluate their applicability to business use cases.

Must-Have Skills

• Strong programming expertise in Python and PySpark
• Hands-on experience with LLMs, RAG, Agentic AI, and Generative AI application development
• Strong experience with Azure OpenAI Service and the Azure AI ecosystem
• Experience building end-to-end AI solutions using Azure Machine Learning
• Knowledge of Prompt Engineering, LLM orchestration, and AI evaluation frameworks
• Experience with Vector Databases (Azure AI Search, Pinecone, Chroma, Weaviate, etc.)Expertise in Machine Learning, Deep Learning, NLP, and model optimization
• Experience building scalable data pipelines, feature engineering, and distributed data processing
• Experience with API development, model deployment, MLOps, monitoring, and CI/CD
• Strong understanding of Responsible AI, AI Governance, and model explainability

Nice-to-Have Skills

• Experience with AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI
• Hands-on experience with Databricks, Azure Data Factory, Synapse Analytics
• Experience with Docker, Kubernetes, and cloud-native architectures
• Knowledge of multi-agent systems, AI observability, and LLM fine-tuning
• Experience building conversational AI, copilots, and enterprise AI solutions
• Exposure to Financial Services / Capital Markets use cases