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Assistant Vice President - Applied AI Engineer

Barclays · Posted Oct 29

Banking, credit card, corporate, investment banking, and wealth management services

Bengaluru and Pune, IndiaFull-timeOnsiteLead/Staff8+ years₹45.0L–₹65.0L yearly100+ applicants
BankingFinancial ServicesInvestment BankingCredit CardsWealth ManagementPublic Company
Full time

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About the role

Barclays is building enterprise AI capabilities, and this role designs and owns AI/ML subsystems including agentic workflows, LLM applications, evaluation pipelines and MLOps tooling. The engineer works between AI architecture and hands-on implementation, delivering secure, scalable production solutions while mentoring junior engineers. The role is based in Bengaluru and Pune.

What you will do

  • 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.
  • 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.

Skills used in this role

What the employer is looking for

  • 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

Preferred qualifications

  • 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)

Benefits and support

  • Compensation and benefits are detailed in the job posting

About Barclays

Barclays logo

Barclays

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Barclays is a British multinational universal bank that provides consumer, corporate, and investment banking, as well as wealth management services. Tracing its origins back to 1690 in London, the institution operates globally to serve millions of retail and institutional clients. The bank leverages cutting-edge technology and digital platforms to drive operational efficiency across its international network.

Industry
Banking
Company size
93000+ employees
Founded
1690
Location
London, United Kingdom
Funding stage
Public Company

Leadership

CV
C.S. Venkatakrishnan

Group Chief Executive

AC
Anna Cross

Group Finance Director

AC
Alistair Currie

Group Chief Operating Officer

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