Pune · Mid Level
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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
Analyst Expectations
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 an AI Engineer at Barclays where you will drive the adoption of Artificial Intelligence and Agentic AI solutions across the organization, enabling intelligent automation, business process transformation, and next-generation digital experiences. You will leverage cutting-edge AI technologies, cloud-native architectures, and scalable deployment platforms to design, build, and operate enterprise-grade AI solutions that deliver measurable business value.
The Hands-on AI Engineer is a core developer responsible for building and maintaining AI-powered applications, intelligent agents, and autonomous workflows. This role requires strong software engineering expertise along with practical experience in Generative AI, Large Language Models (LLMs), Agentic AI frameworks, FastAPI-based services, and AWS cloud technologies. Engineers will design AI orchestration workflows, integrate enterprise data sources, implement RAG pipelines, and ensure secure, scalable, and production-ready AI solutions.
To be successful as an AI Engineer, you should have experience with:
Strong proficiency in Python with a solid understanding of modern software engineering principles and best practices.
Hands-on experience building AI applications using FastAPI and RESTful microservices architectures.
Experience working with Large Language Models (LLMs) and Generative AI platforms such as Claude, Amazon Bedrock, or similar technologies.
Strong understanding of Agentic AI concepts, multi-agent systems, and AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, LangChain, or similar.
Experience designing and implementing Retrieval Augmented Generation (RAG) solutions using vector databases and embeddings.
Hands-on experience with AWS services including Bedrock, Lambda, ECS/EKS, S3, DynamoDB, API Gateway, CloudWatch, and IAM.
Experience integrating AI solutions with enterprise data platforms, APIs, databases, and knowledge repositories.
Knowledge of prompt engineering, model evaluation, guardrails, and AI governance best practices.
Experience with containerisation and deployment technologies such as Docker, Kubernetes, and CI/CD pipelines.
Some other highly valued skills may include:
Understanding of SWIFT messaging formats (ISO 20022 or MT messages)
Experience with IBM MQ or JMS-based messaging
Knowledge of payment processing domain
Familiarity with ELK stack for logging and troubleshooting
Experience with SWIFT parsing libraries (Prowide Core)
You may be assessed on 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.
The role is based out of Pune.
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