Barclays About the Company :

Barclays is a leading British universal bank and global financial services institution with a history of more than 300 years. The group provides a broad range of financial services across consumer banking, corporate banking, investment banking, wealth management, and payments.

Barclays operates across 38 countries with around 100,000 colleagues globally, serving millions of customers and clients. Its purpose is Working together for a better financial future.

In India, Barclays has established technology and operations capabilities supporting areas such as data, cloud, AI, analytics, technology, and financial services, making India an important location for the group's global operations.

Position : AWS GenAI Senior Expert

Location : Bangalore / Pune

Experience : 5 Years

Employment Type : Full time

About the Role :

We are looking for a highly skilled AWS GenAI Senior Expert with strong hands-on experience in Generative AI, AWS Bedrock, LLMs, AI Agents, MCP, RAG, and Vector Databases. The candidate will be responsible for designing and delivering end-to-end, enterprise-grade GenAI solutions and will work closely with technical and business stakeholders to drive AI innovation, proof-of-concepts, and adoption initiatives. The ideal candidate should have strong expertise in Python and AWS cloud-native architectures, along with a solid understanding of AI security, governance, model evaluation, observability, and scalable AI deployments.

Key Responsibilities :

- Design, develop, and implement end-to-end Generative AI solutions using AWS services.
- Build and deploy solutions using AWS Bedrock, LLMs, RAG, AI Agents, MCP, and Vector Databases.
- Design and implement multi-agent AI systems and intelligent AI-powered applications.
- Develop RAG pipelines, semantic search solutions, NLP pipelines, and enterprise AI applications.
- Build scalable and serverless architectures using AWS Lambda, ECS, Step Functions, OpenSearch, RDS, and other AWS services.
- Develop and integrate REST APIs for AI and cloud-based applications.
- Design and implement vector search and knowledge retrieval solutions using vector databases and Amazon OpenSearch.




- Develop model monitoring, evaluation, and observability frameworks to ensure performance, reliability, and scalability.
- Implement Infrastructure as Code using AWS CloudFormation.
- Design secure GenAI solutions with appropriate AI guardrails, PII protection, access controls, and governance frameworks.
- Implement mechanisms for prompt security, responsible AI, model safety, and data protection.
- Evaluate LLM performance, response quality, accuracy, latency, and cost.
- Drive AI cost optimization across models, infrastructure, and workloads.
- Build containerized AI applications and deploy them using scalable cloud architectures.
- Establish monitoring and observability practices for production AI workloads.
- Lead PoCs, technical evaluations, and enterprise AI adoption initiatives.
- Collaborate with architects, engineering teams, product teams, and business stakeholders to translate business requirements into scalable AI solutions.
- Provide technical leadership, conduct design discussions, and contribute to AI engineering best practices.
- Stay updated with emerging developments in GenAI, Agentic AI, LLMs, AWS AI services, and AI security.

Required Technical Skills :

1. Generative AI &

- LLM :
- AWS Bedrock
- Large Language Models (LLMs)
- Generative AI
- AI Agents / Agentic AI
- MCP (Model Context Protocol)
- RAG (Retrieval-Augmented Generation)
- Semantic Search
- NLP
- Prompt Engineering
- LLM Evaluation

2. AWS &

- Cloud :
- AWS Lambda
- Amazon ECS
- AWS Step Functions
- Amazon OpenSearch
- Amazon RDS
- AWS CloudFormation
- AWS serverless and cloud-native architecture
- AWS security and IAM concepts

3. Development :

- Python 5 years
- REST API development
- Microservices architecture
- Containerization
- Scalable application development

4. Data &





- AI Infrastructure :
- Vector Databases
- Embeddings
- Knowledge Retrieval Systems
- AI/NLP Pipelines
- Model Monitoring
- Observability
- Performance Optimization

AI Security &

- Governance :
- AI security and responsible AI practices
- LLM security and prompt injection risks
- AI Guardrails
- PII protection and data privacy
- Model governance
- Access control and secure AI architecture
- Model evaluation and quality monitoring
- Cost optimization and responsible cloud usage

Key Requirements :

- 5 years of experience in Python development.
- 3 years of hands-on AWS experience.
- Strong practical experience in Generative AI and LLM-based application development.
- Hands-on experience with AWS Bedrock is mandatory.
- Strong understanding of RAG, AI Agents, MCP, vector databases, and semantic search.
- Experience designing serverless and cloud-native architectures.
- Experience with containerization and production-grade AI deployments.
- Strong REST API development experience.
- Experience with Infrastructure as Code, preferably AWS CloudFormation.
- Strong problem-solving and analytical skills.
- Excellent stakeholder management and communication skills.
- Ability to independently drive technical PoCs and enterprise AI initiatives.

Preferred Skills :

- Experience building multi-agent systems.
- Experience with enterprise GenAI implementations.
- Experience with LLM evaluation and model monitoring.
- Knowledge of AI governance and responsible AI frameworks.
- Experience with cloud observability and production monitoring.
- Experience working in large enterprise or BFSI environments.
- Ability to communicate complex AI concepts to both technical and non-technical stakeholders.

Ideal Candidate :

The ideal candidate will be a hands-on GenAI/AWS specialist who can take an AI use case from concept and PoC through architecture, development, deployment, security, monitoring, and production adoption. The candidate should combine strong Python AWS GenAI expertise with excellent leadership, communication, stakeholder management, and enterprise solutioning capabilities.

📌 AWS Generative AI Engineer (India)
🏢 Talent Checkers
📍 India