Enterprise AI Architect

State Bank of India; Mumbai; On-site; INR 8,100,000 - 9,900,000; Full time

Job summary

State Bank of India is seeking an Enterprise AI Architect to lead GPU‑based AI infrastructure design and the end‑to‑end deployment of Generative AI and LLM solutions. You will shape data platforms, model serving, and integration strategies across units with strong governance.

You will drive ML Ops and security practices, ensuring responsible AI deployments while aligning with BFSI regulatory standards and enterprise goals.

Qualifications

• Mandatory: Bachelor's / Master's degree in Computer Science, Information Technology, Engineering, Data Science, AI or equivalent discipline.
• TOGAF certification is preferred.
• Any certification on Enterprise AI Architecture covering end to end solution designed for AI / ML and digital platforms will be an added advantage.

Responsibilities

• Design and optimize GPU infrastructure and workload architectures, using NVIDIA AI Enterprise for high‑performance AI apps.
• Lead the architectural design and implementation of Generative AI and LLM solutions, including RAG and vector databases.
• Develop robust architectures for agentic AI systems, model gateways, and efficient model serving mechanisms.
• Establish and enforce ML Ops / LLM Ops pipelines for deployment, monitoring, and lifecycle management of AI models.
• Architect secure and scalable enterprise data platforms that support diverse AI initiatives with governance.
• Design API and integration strategies for AI services across business units and applications.
• Implement AI security measures, responsible AI principles, and model governance frameworks.

Skills

Generative AI

LLM architectures

GPU design

ML Ops

Security & governance

Education

Bachelor's / Master's degree in CS/IT/Engineering/Data Science/AI

Tools

TOGAF certification

Enterprise AI Architecture certification

Job description

Position- Enterprise AI Architect at State Bank of India (SBI)

Contract - 3 years extendable to 5 years

CTC - 90 LPA

Educational Qualification (As on 30.09.2026)

Mandatory: Bachelor's / Master's degree in Computer Science, Information Technology, Engineering, Data Science, AI or equivalent discipline.

Preferred Certifications:

• TOGAF certification.
• Any certification on Enterprise AI Architecture covering end to end solution designed for AI / ML and digital platforms will be an added advantage.

Post Qualification Work Experience (As on 30.09.2026)

Minimum 8 years of overall technology experience, including at least 3 years in enterprise, platform, data or AI architecture with experience in large-scale AI/ML environments, preferably in BFSI or another regulated industry.

Responsibilities:

• Design and optimize GPU infrastructure and workload architectures, specifically leveraging the NVIDIA AI Enterprise ecosystem for high-performance AI applications.
• Lead the architectural design and implementation of Generative AI and Large Language Model (LLM) solutions, incorporating advanced techniques such as Retrieval Augmented Generation (RAG) and vector databases.
• Develop robust architectures for agentic AI systems, model gateways, and efficient model serving mechanisms.
• Establish and enforce ML Ops / LLM Ops pipelines and practices to ensure seamless deployment, monitoring, and lifecycle management of AI models.
• Architect secure and scalable enterprise data platforms that support diverse AI initiatives, ensuring data quality, accessibility, and governance.
• Design API and integration strategies for AI services, enabling seamless consumption across various business units and applications.
• Implement comprehensive AI security measures, responsible AI principles, and robust model governance frameworks to ensure ethical and compliant AI deployments.