AI Data Engineer

Purpose of the role

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. 

Accountabilities

• Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
• Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
• Development of processing and analysis algorithms fit for the intended data complexity and volumes.
• Collaboration with data scientist to build and deploy machine learning models.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

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.

Join us as a “AI Data Engineer" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.
You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.

To be successful as a “AI Data Engineer", you should have experience with:

  Basic/ Essential Qualifications:

• Design, build, and deploy AI/ML solutions on AWS from experimentation to production.

• Develop and productionize LLM-based applications, including prompt design, chaining, and evaluations.

• Leverage AWS AI/ML services to build scalable solutions, including:

  • Amazon SageMaker (training, pipelines, endpoints, monitoring).

  • Amazon Bedrock (foundation models, prompt engineering, guardrails, agents).

• Implement MLOps best practices: model versioning, CI/CD, monitoring, rollback, and reproducibility.

• Build secure and compliant AI systems using IAM, KMS, private networking, VPC endpoints.

• Optimize inference cost, latency, and scalability (autoscaling, batching, async inference).

• Collaborate with stakeholders to identify AI use cases and translate them into technical solutions.

• Ensure responsible AI practices, including explain ability, bias awareness, and governance.

Desirable skillsets/ good to have:

• Strong experience in AI / Machine Learning concepts and applied use cases.

• Solid programming skills in Python for ML and AI workloads.

• Hands-on experience with AWS AI/ML services, especially.

• Amazon SageMaker.

• Amazon Bedrock.

• Experience working with LLMs, embeddings, vector search, and RAG architectures.

• Familiarity with ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, etc.)

• Strong understanding of model lifecycle management and MLOps patterns.

• Knowledge of cloud-native architecture and scalable system design on AWS.

• Experience implementing security and compliance controls for AI workloads.

This role will be based out of Pune.