Senior AI & Data Engineer

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 :

1. Azure Databricks and all its capabilities

2. Azure Data Factory

3. Azure AI Foundry

4. Azure OpenAI

5. Azure Storage (ADLS/Blob)

6. Azure Functions

7. 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.