Job Summary :

We are looking for a senior technology professional with deep expertise across Data Engineering, Artificial Intelligence, and Generative AI.

The role will be responsible for designing and implementing scalable data and AI platforms that enable enterprise analytics, machine learning, and GenAI applications.

The candidate will work across data architecture, data engineering, AI/ML pipelines, LLM applications, and modern data platforms while providing technical leadership to engineering teams.

Key Responsibilities :

- Define architecture and technical strategy for enterprise data and AI platforms.

- Design scalable data pipelines supporting AI/ML and Generative AI use cases.

- Build and modernize data ingestion, processing, transformation, and serving architectures.

- Design data platforms capable of supporting structured and unstructured data.

- Develop data pipelines required for machine learning and GenAI applications.

- Build data foundations for RAG, LLM, AI agents, recommendation systems, and predictive models.

- Design data architectures integrating data lakes, warehouses, databases, APIs, and enterprise applications.

- Work with AI/ML teams to prepare high-quality datasets for model training and inference.

- Design data pipelines for document processing, embeddings, vector search, and knowledge retrieval.

- Establish data quality, governance, lineage, security, and access-control standards.

- Evaluate modern data engineering and AI technologies.

- Drive optimization of data processing, pipeline performance, scalability, and cost.

- Provide technical leadership to data engineers, AI engineers, and architects.

- Collaborate with enterprise architecture, engineering, product, and business teams.

- Drive POCs and production implementation of emerging AI and GenAI technologies.

- Ensure reliability, observability, security, and operational readiness of data and AI platforms.

Required Skills :

- 15 to 22 years of experience in data engineering, software engineering, AI/ML, or technology architecture.

- Strong expertise in Python and data engineering technologies.

- Extensive experience designing enterprise-scale data platforms and pipelines.

- Strong understanding of SQL, data modeling, ETL/ELT, distributed data processing, and data architecture.

- Strong experience with AI/ML concepts and production AI systems.

- Hands-on experience with Generative AI, LLMs, RAG, embeddings, vector databases, and AI agents.

- Experience integrating data platforms with AI/ML applications.

- Strong understanding of cloud-native data and AI architectures.

- Experience with data governance, security, quality, lineage, and lifecycle management.

- Strong technical leadership and architecture skills.