Senior AI & Data Engineer (Remote, India)

We are seeking an experienced Senior AI & Data Engineer to design, build, and deliver enterprise-scale Data & AI solutions on Azure. This role combines expertise in Data Engineering, AI/Generative AI, Cloud Architecture, and Solution Design , supporting the full lifecycle from data ingestion and platform engineering to ML/GenAI deployment and operations.

Key Responsibilities

• Design and implement scalable Data & AI platforms, applications, and services.
• Build and optimize data pipelines, ETL/ELT processes, and analytics solutions.
• Develop AI and Generative AI solutions using Azure AI services, Azure OpenAI, Azure AI Foundry, Agentbricks , Genie Spaces and modern AI frameworks.
• Implement RAG architectures, AI agents, orchestration frameworks, and LLM-powered applications.
• Design and maintain data lake, Lakehouse, and warehouse solutions.
• Apply best practices for security, governance, compliance, guardrails, monitoring, and Responsible AI.
• Implement CI/CD, DevOps, Infrastructure as Code (IaC), and operational excellence practices.
• Collaborate with business stakeholders, architects, data scientists, and engineering teams to deliver business value.
• Provide technical leadership, mentorship, and architectural guidance.

Required Qualifications

Technical Skills

• Expert-level Python and strong SQL skills.
• Hands-on experience with PySpark , distributed data processing, and enterprise data engineering.
• Experience building APIs, microservices, and cloud-native applications.
• Strong experience with:
• Azure Databricks and all its capabilities
• Azure Data Factory
• Azure AI Foundry
• Azure OpenAI
• Azure Storage (ADLS/Blob)
• Azure Functions
• Azure DevOps

AI & Data

• Experience delivering production-grade AI, ML, and Generative AI solutions.
• Knowledge of LLMs, RAG, vector databases, embeddings, AI agents, and orchestration frameworks (LangChain, Semantic Kernel, LangGraph , Ontology).
• Strong understanding of data platforms, data modeling, governance, and enterprise analytics architectures.
• Familiarity with MLOps, AI governance, Responsible AI, and AI lifecycle management.

DevOps & Security

• Experience with CI/CD, Git, Azure DevOps, IaC, and DevSecOps.
• Understanding of cloud security, identity management, API security, and enterprise architecture principles.
• Knowledge of governance and compliance frameworks (GXP , SOX)

Soft Skills

• Strong communication, problem-solving, and stakeholder management skills.
• Ability to translate business requirements into scalable technical solutions.
• Self-driven, collaborative, and capable of leading technical initiatives and influencing architectural decisions.