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Lead AI Engineer

lead · Artificial Intelligence

Job Description

Purpose of the role

To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. 

Accountabilities

• Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.
• Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.
• Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
• Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth.
• Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
• Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.

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 Barclays as a Lead AI Engineer role, where you will design and build core AI/ML solutions that power our enterprise AI capabilities. You will take ownership of significant AI subsystems — from agentic workflows and LLM applications to evaluation pipelines and MLOps tooling — delivering production-grade solutions that are secure, scalable, and aligned with our architectural vision. You bridge the gap between AI architecture and hands-on implementation, driving technical delivery while mentoring junior engineers. At Barclays, we don't just anticipate the future - we're creating it.

To be successful in this role, you should have below skills:

• Bachelor's degree (or above) in Computer Science, Engineering, Mathematics, or related discipline

• 8+ years software engineering experience with at least 3 years building AI/ML systems, scalable ML infrastructure, or model serving platforms at enterprise scale

• Strong proficiency in Python (FastAPI, asyncio) and/or Go/Java, with production experience building APIs and microservices serving high-throughput, low-latency workloads

• Hands-on experience developing agentic AI systems and LLM applications including multi-agent orchestration, tool use, planning frameworks, and deployment of multi-step AI workflows

• Solid technical knowledge of prompt engineering, RAG architectures, and modern agentic frameworks (Strands, LangGraph, Google ADK) with ability to build and optimise agent-based solutions

• Working experience with GenAI/LLM systems — prompt engineering, retrieval-augmented generation, model serving (vLLM), and OpenAI-compatible API surfaces

• Strong understanding of distributed systems architecture — microservices, cloud platforms, API design (REST, gRPC, OpenAPI), and event-driven architectures

• Experience with AWS services — EC2/EKS, S3, IAM, RDS, and at least one AI service (Bedrock, SageMaker)

• Hands-on experience with Docker and Kubernetes — containerising applications and deploying to orchestrated environments

• Experience with CI/CD pipelines, Infrastructure-as-Code (CloudFormation, Terraform), and observability tools (OpenTelemetry, distributed tracing)

• Ability to work on system design from ideation through completion with limited supervision; effective communication with both technical and non-technical stakeholders

Some other highly valued skills may include below:

• Experience building evaluation frameworks for agentic systems including agent benchmarking, reasoning traces, and monitoring observability for multi-step AI workflows in production

• Experience in vector databases, knowledge graphs, semantic search, and memory systems for stateful agents with understanding of retrieval optimisation and context management

• Experience implementing AI safety controls — content filtering, guardrails, prompt injection detection, PII redaction

• Knowledge of AI security frameworks — NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10

• Familiarity with model fine-tuning techniques (LoRA, RLHF, supervised fine-tuning) for domain-specific SLMs

• Knowledge of responsible AI practices, model governance, and security considerations for autonomous systems

• Understanding of Zero Trust architecture and identity systems (EntraID, OAuth2/OIDC)

• Background in financial services — understanding of regulatory requirements, data residency, and compliance obligations

• Experience with GPU workload management and inference optimisation (vLLM)

You may be assessed on the key critical skills relevant for success 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 in Bengaluru and Pune office.