Full-Time

AI Engineer

Barclays

Barclays

10,001+ employees

Wealth management services for UK clients

No salary listed

Pune, Maharashtra, India + 1 more

More locations: Bengaluru, Karnataka, India

Remote

Based in the Bengaluru and Pune offices.

Bachelor's

Category
AI & Machine Learning (1)
Required Skills
LLM
Kubernetes
Microsoft Azure
FastAPI
Python
Distributed Systems
Software Testing
Machine Learning
Java
Docker
RAG
Microservices
AWS
Go
Risk Management
LangGraph

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Requirements
  • A Bachelor's degree or above in Computer Science, Engineering, Mathematics, or a related discipline is required.
  • At least 12 years of software engineering experience, or experience designing and building scalable machine-learning infrastructure, model-serving platforms, and end-to-end machine-learning operations systems at enterprise scale, is required.
  • Expert-level proficiency in Python, including FastAPI and asynchronous patterns, and/or Go or Java is required, with demonstrable experience building production systems serving high-throughput, low-latency workloads.
  • Strong experience developing agentic artificial-intelligence systems and large-language-model applications, including multi-agent orchestration, tool use, planning frameworks, and production deployment of multilayered artificial-intelligence workflows at scale, is required.
  • Deep technical knowledge of large-language-model fine-tuning, prompt engineering, retrieval-augmented-generation architectures, and modern agentic frameworks including Strands, LangGraph, and Google ADK is required.
  • Hands-on experience with generative-artificial-intelligence and large-language-model systems, including prompt engineering, loop engineering, retrieval-augmented generation, model serving with vLLM, and OpenAI-compatible application programming interfaces, is required.
  • Experience with Amazon Web Services services including EC2/EKS, S3, IAM, RDS, and at least one artificial-intelligence service such as Bedrock or SageMaker is required.
  • Hands-on experience with Docker and Kubernetes is required for containerizing applications and deploying them to orchestrated environments.
  • Experience with distributed-systems architecture, including microservices, cloud platforms, active-active replication, failover strategies, and data-consistency patterns, is required.
  • The candidate must be able to communicate complex technical architectures to senior leadership and cross-functional stakeholders.
Responsibilities
  • Design, develop, and improve software that provides business, platform, and technology capabilities for customers and colleagues.
  • Develop and deliver high-quality, scalable, maintainable, and performance-optimized software solutions using industry-aligned programming languages, frameworks, and tools.
  • Collaborate with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration with business objectives.
  • Participate in code reviews and promote code quality and knowledge sharing.
  • Stay informed about technology trends and innovations and contribute to technology communities.
  • Apply secure coding practices to mitigate vulnerabilities, protect sensitive data, and deliver secure software solutions.
  • Implement effective unit-testing practices to ensure code design, readability, and reliability.
  • Design, build, and scale artificial-intelligence and machine-learning solutions, including agentic artificial-intelligence systems, large-language-model applications, and end-to-end machine-learning operations pipelines.
  • Shape architectural decisions and ensure artificial-intelligence solutions provide enterprise-grade reliability, security, and governance.
  • Guide technical direction as a subject-matter expert, lead collaborative multi-year assignments, and guide team members through structured assignments.
  • Train, guide, and coach less experienced specialists.
  • Advise key stakeholders, functional leadership teams, and senior management on functional and cross-functional areas of impact and alignment.
  • Manage and mitigate risks through assessment in support of control and governance objectives.
  • Demonstrate leadership and accountability for managing risk and strengthening controls related to the team's work.
  • Create solutions through sophisticated analytical evaluation of complex alternatives, define problems, and develop innovative solutions.
  • Incorporate extensive research into problem-solving processes.
  • Build and maintain trusting relationships and partnerships with internal and external stakeholders to accomplish business objectives.
Desired Qualifications
  • Experience building evaluation frameworks for agentic systems, including agent benchmarking, reasoning traces, and monitoring observability for multi-step artificial-intelligence workflows in production.
  • Experience with vector databases, knowledge graphs, semantic search, and memory systems for stateful agents, including retrieval optimization and context management.
  • Experience building artificial-intelligence safety and guardrail systems, including content filtering, prompt-injection detection, personally identifiable information redaction, and toxicity detection.
  • Knowledge of artificial-intelligence security frameworks including NIST AI RMF, MITRE ATLAS, and OWASP LLM Top 10.
  • Experience with model fine-tuning methods including LoRA, reinforcement learning from human feedback, and supervised fine-tuning for domain-specific small language models.
  • Knowledge of responsible artificial-intelligence practices, model governance, and security considerations for autonomous systems.
  • A background in financial services, including understanding of regulatory requirements, data residency, and compliance obligations.
  • Experience with policy engines such as OPA/Rego and zero-trust identity models with OAuth2/OIDC, including Entra ID/Azure AD.
  • Experience with cost-attribution and chargeback models for shared artificial-intelligence infrastructure platforms.

Barclays Wealth Management provides personalized wealth management services to clients across the UK through a regional network of financial experts. It delivers tailored investment management, financial planning, and estate and trust services, based on each client’s goals, risk tolerance, and time horizon, with support from Barclays’ broader banking resources. The company differentiates itself through its scale and integration, combining local, face-to-face guidance with the back‑end support and product access of a large UK bank. Its goal is to help clients preserve and grow their wealth over the long term while managing risk through a comprehensive, advisor-led service.

Company Size

10,001+

Company Stage

IPO

Headquarters

London, United Kingdom

Founded

1690

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Simplify Jobs

Simplify's Take

What believers are saying

  • July 2026 Barclays raised 2026 income guidance to about £31.5 billion.
  • April 2026 FCA selected Barclays for AI Live Testing, accelerating product experimentation.
  • September 2026 wealth hiring in Manchester, Liverpool, and Glasgow signals continued client-growth investment.

What critics are saying

  • March 2026 FCA fined Barclays £40 million over the 2008 Qatar fundraising.
  • Barclays withdrew its Upper Tribunal appeal, leaving reputational damage unresolved into 2027.
  • Rogo’s $30 million bank-backed AI platform automates banking tasks Barclays still pays staff for.

What makes Barclays unique

  • Barclays Wealth Management combines UK branch coverage with mobile-app investing.
  • January 2026 FactSet agreement strengthens Barclays’ market-data infrastructure and analytics.
  • September 2026 Japan rehiring shows Barclays can re-enter niche trading franchises.

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