- About Us
- Business Areas
- Early Careers
- Locations
Your jobs
Date live:
Mar. 19, 2026
Business Area:
USCB Operations India
Area of Expertise:
Data & Analytics
Reference Code:
JR-0000072906
Contract:
Permanent
Take a look at the map to see what’s nearby. Train stations & bus stops, gyms, restaurants and more.
Explore locationEmbark on a transformative journey as Vice President-ML Ops Engineer at Barclays, where you will play a pivotal role to manage operations within a business area and maintain processes with risk management initiatives. You will take ownership of your work and provide first-class support to our clients with expertise and care.
Purpose of the role:
To lead the design, implementation, and governance of enterprise-grade ML Ops frameworks that enable scalable, secure, and efficient deployment of AI and Generative AI models, while driving best practices in automation, monitoring, and AWS architecture.
Accountabilities are given below:
Lead and mentor a high‑performing ML Ops engineering team, driving ownership, skill development, and cross‑functional collaboration across Data Science, Engineering, Cloud, and Security.
Architect and govern scalable, secure, and cost‑optimized AWS platforms (SageMaker, EKS, Lambda, Step Functions) for enterprise ML and GenAI workloads.
Design and implement automated ML pipelines covering data ingestion, management, feature processing, and high‑throughput model training/inference workflows, ensuring reliable, low‑latency, production‑grade consumption patterns.
Establish robust data and model governance frameworks, including quality checks, lineage, auditability, and regulatory compliance.
Build comprehensive model observability and monitoring systems for performance, drift, data quality, latency, and operational health using CloudWatch and custom dashboards.
Drive security, reliability, and operational excellence, ensuring strong IAM practices, encryption, secrets management, and cloud cost optimization.
Technical skills required for this role include:
Experience in Programming & Automation: Python, Bash, SQL.
MLOps Tools: MLflow, Kubeflow, AWS SageMaker Pipelines
Cloud Platforms: AWS (SageMaker, Bedrock, Lambda, Step Functions, CloudWatch)
DevOps Expertise: CI/CD (GitHub Actions, Jenkins), Docker, Kubernetes
Data Management: Enterprise data governance, ETL processes
Leadership Skills: Strategic planning, team management, stakeholder communication
The VP-MLOps Engineer role is responsible for leading the design and governance of MLOps frameworks, AWS-based architectures, and automation strategies to enable efficient, secure, and scalable deployment of AI and Generative AI models.
This role requires a flexible working approach, ensuring availability during select hours that overlap with US-based partners and stakeholders.
You may be assessed on key essential skills relevant to succeed in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.
This role is based out of Noida.
Purpose of the role
To develop and lead the execution of business unit/function data strategy, ensuring the effective and efficient use of data to drive informed decision-making, support regulatory and control requirements, improve operational efficiency, and generate business value.
Accountabilities
Vice President Expectations
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.