Senior AI ML Engineer

Senior AI/ML Engineer

We are seeking an experienced Senior AI/ML Engineer to design, develop, and deploy enterprise-scale AI and Machine Learning solutions. The ideal candidate will have strong expertise in Databricks, Azure AI Foundry, Applied AI, ML Engineering, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and MLOps. This role requires leading the complete AI lifecycle from experimentation through production deployment while delivering scalable, secure, and high-performing AI solutions in cloud environments.

Key Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions for enterprise applications.
• Lead the complete AI lifecycle, including experimentation, model development, deployment, monitoring, and continuous improvement.
• Build, optimize, and deploy predictive machine learning models and LLM-powered RAG (Retrieval-Augmented Generation) and Agentic AI solutions.
• Translate business requirements into AI-driven solutions, measurable KPIs, and scalable architectures.
• Design and implement vector databases, embeddings, semantic search, and orchestration frameworks.
• Develop scalable APIs and model-serving solutions using FastAPI, MLflow, and related technologies.
• Optimize AI models for performance, scalability, latency, reliability, and cost efficiency.
• Implement CI/CD pipelines, containerized deployments, and cloud-native AI solutions.
• Establish MLOps practices, including model monitoring, drift detection, retraining, versioning, and lifecycle management.
• Evaluate AI model performance using automated testing and human-in-the-loop validation techniques.
• Ensure Responsible AI, governance, security, compliance, and enterprise best practices.
• Collaborate with business stakeholders, architects, data engineers, and product teams to deliver AI initiatives.
• Mentor junior engineers and provide technical leadership across AI/ML projects.

Required Skills & Experience

• Strong hands-on experience with Databricks and Azure AI Foundry.
• Expertise in Machine Learning Engineering and Applied AI.
• Experience deploying production-grade AI/ML solutions.
• Strong knowledge of Retrieval-Augmented Generation (RAG) and Agentic AI architectures.
• Proficiency in Python programming.
• Experience with FastAPI, MLflow, or similar model-serving frameworks.
• Hands-on experience with vector databases, embeddings, and semantic search.
• Experience using LangChain, LlamaIndex, or similar AI orchestration frameworks.
• Strong understanding of CI/CD pipelines, containerization (Docker/Kubernetes), and cloud deployment.
• Experience with predictive machine learning models and AI evaluation methodologies.
• Knowledge of MLOps, model monitoring, drift detection, retraining, and lifecycle management is preferred.
• Experience working in regulated or high-compliance environments is preferred.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.

Technical Skills

• Databricks
• Azure AI Foundry
• Python
• Machine Learning
• Applied AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI
• FastAPI
• MLflow
• LangChain
• LlamaIndex
• Vector Databases
• Embeddings
• CI/CD
• Docker
• Kubernetes
• Cloud Deployment
• MLOps
• Model Monitoring
• Drift Detection
• AI Governance

Managerial Skills

• Technical Leadership
• Mentoring & Coaching
• Cross-functional Collaboration
• Solution Architecture
• Ownership & Accountability
• Innovation & Continuous Learning
• Responsible AI Governance

Primary Skills (PS)

Databricks, Azure AI Foundry, Python, RAG, Agentic AI, FastAPI, MLflow, LangChain, LlamaIndex, MLOps.