Vice President AI Engineer

Join Barclays as a Vice President AI Engineer role, where you will serve as a senior engineer helping to drive adoption of state-of-the-art AI technologies. You'll use your expertise to design, build, and scale AI/ML solutions from agentic AI systems and LLM applications to end-to-end MLOps pipelines enabling the bank's success across multiple business units. You will shape architectural decisions, mentor engineering teams, and ensure our AI solutions meet the demands of enterprise-grade reliability, security, and governance. 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

12+ years software engineering experience or experience designing and building scalable ML infrastructure, model serving platforms, and end-to-end MLOps systems at enterprise scale

Expert-level proficiency in Python (FastAPI, async patterns) and/or Go/Java, with demonstrable experience building production systems serving high-throughput, low-latency workloads

Strong experience developing agentic AI systems and LLM applications including multi-agent orchestration, tool use, planning frameworks, and production deployment of multi-layered AI workflows at scale

Deep technical knowledge of LLM fine-tuning, prompt engineering, RAG architectures, and modern agentic frameworks (Strands, LangGraph, Google ADK) with validated ability to architect and optimise agent-based solutions

Hands-on experience with GenAI/LLM systems prompt engineering, loop engineering, retrieval-augmented generation, model serving (vLLM), and OpenAI-compatible API surfaces

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 distributed systems architecture microservices, cloud platforms, active-active replication, failover strategies, and data consistency patterns

Proven ability to communicate complex technical architectures to senior leadership and cross-functional 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 building AI safety/guardrails systems content filtering, prompt injection detection, PII redaction, toxicity detection

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

Experience with model fine-tuning (LoRA, RLHF, supervised fine-tuning) for domain-specific SLMs

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

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

Experience with policy engines (OPA/Rego) and zero-trust identity models with OAuth2/OIDC (EntraID/Azure AD)

Experience with cost attribution and chargeback models for shared AI infrastructure platforms

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.

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 organizations 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.

Vice President Expectations

To contribute or set strategy, drive requirements and make recommendations for .