Senior AI Platform & Delivery Lead

Jobitus; Ahmedabad District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Jobitus in India is seeking a Senior AI Platform & Delivery Lead to own the secure, production-ready AI deployment path within the bank's in-country environment. You will shepherd on-prem sovereignty, data residency, and drive fast, auditable deployment through a vendor-ecosystem.

Your remit spans MLOps, platform governance, and direct management of vendor delivery to ensure security, compliance and timely integrations.

Qualifications

• 10+ years in platform/DevOps/MLOps or AI engineering, with production deployment experience.
• Hands-on Kubernetes, Docker/containerisation, and container security in production.
• On-premise/sovereign/in-region deployment experience with strict data residency.
• Proven vendor management and integration of third-party AI systems.
• Experience reading vendor architectures and identifying feasibility, not bluffing.

Responsibilities

• Own the AI deployment pipeline from Dev to Production with a governed path.
• Serve as technical owner for vendor delivery and ensure security and residency compliance.
• Lead security, integration, and governance, including IVA/scan processes where applicable.
• Establish reusable deployment patterns to accelerate future use cases.

Skills

Vendor management

In-region deployment

Data residency

MLOps

Production deployment

Tools

Kubernetes

Docker / containerisation

Container security

Job description

Senior AI Platform & Delivery Lead

Unit: Innovation, Emerging Technologies & Digital Partnerships

Reports to: Head of Innovation, Emerging Technologies & Digital Partnerships

Level: Senior / Specialist (10+ years)

Purpose ofthe role

Own the path that takes AI from a delivered solution to a secured, monitored production

system running in-country — and make that path fast. With delivery partner-led, this role is

the bank's technical owner of vendor delivery and deployment: it holds vendors to the

bank's security, residency and quality standards, integrates their solutions into our

environment, and ensures the bank is never dependent on a vendor's pace or claims.

This is the role that turns a blocked pipeline into a working one. Its single measure of

success is deployment speed — how quickly validated AI reaches production, safely.

Key responsibilities

Deployment & platform

• Own the AI deployment pipeline (Dev → UAT → Production) and the sandbox
• environment, ensuring a clear, governed, repeatable path to production.
• Operate and govern the on-prem / sovereign AI platform (Kubernetes,containerisation, GPU orchestration) — configuring and managing it, includingpartner-provided components.
• Establish a reusable "golden path" deployment pattern so each successive use case ships faster than the last.

Vendor & delivery management

• Act as the technical counterpart to AI vendors and the implementation partner —
• review their architectures, challenge unrealistic timelines, and hold them to delivery commitments.
• Validate that vendor-delivered solutions (container images, models, integrations)meet the bank's security and residency requirements before deployment.
• Set the technical standards every vendor must deliver to, so solutions arrive in a form our environment can actually run.

Security & integration

• Work directly with Information Security (ISO) to enable and run container image vulnerability and malware scanning (IVA/MSB) for AI workloads.
• Work with IT Infrastructure to provision, scale and govern compute for AI workloads.
• Own the integration of third-party AI products into the bank's systems and data.

MLOps & governance

• Stand up and run model registry, versioning, monitoring and drift detection — so models stay accountable after go-live, not just at delivery.
• Ensure all AI in production is observable, auditable and aligned to CBO and risk expectations.

Must-have experience

• 10+ years in platform / DevOps / MLOps or AI engineering, with a track record of
• putting solutions into live production
• Hands-on Kubernetes, Docker / containerisation, and container security in production.
• On-premise / sovereign /in-region deployment experience — not cloud-only.
• Data residency is non-negotiable.
• Proven management of software / AI vendors and integration ofthird-party
• systems — ideally in a bank, telco or government.
• Able to read a vendor's architecture and identify what will not work — strong enough technically not to be bluffed.
• Experienced in managing AI Projects, as a project manager

Nice to have

• GPU infrastructure sizing and cost optimisation.
• Feature stores and data pipelines (to also support the data-foundation work).
• GCC / Arabic-region or regulated-financial-services experience.