Senior GenAI and Python Developer – AVP

About the role

At Barclays, our vision is to redefine the future of banking and deliver innovative solutions. As a Senior GenAI and Python Developer – AVP, you will leverage your deep AWS expertise to help a large cross-functional team deliver multiple Generative AI solutions each year. These solutions will directly impact both end users and the business by reducing manual effort, streamlining workflows, and accelerating key processes.

Responsibilities

• Leverage Python 3.12+ and LangChain, machine learning frameworks, the Amazon Bedrock SDK, and related AI/ML technologies to develop transformative AI technologies.
• Develop and deploy FastAPI-based applications, integrating with frontend/client integration and API consumption patterns.
• Design and build Agentic RAG (Retrieval-Augmented Generation) solutions and multi-agent AI systems using industry-standard frameworks and best practices.
• Monitor, evaluate, and optimize GenAI application performance and costs using observability tools like Langfuse and Phoenix.
• Collaborate with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration with business objectives.
• Stay informed of industry technology trends and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth.
• Implement effective unit testing practices to ensure proper code design, readability, and reliability.

Requirements

• Practical development experience with Python 3.12+ and extensive AWS experience, including services like Amazon EKS, Amazon Bedrock, Knowledge Bases, CloudWatch, AgentCore, Strands SDK, Auto Scaling Groups, Load Balancers, API Gateway, Lambda, Step Functions, AWS Glue, PostgreSQL, and Amazon RD.
• Experience with FastAPI-based applications and frontend/client integration.
• Experience with observability and FinOps tools, such as Langfuse and Phoenix.
• Experience designing and building Agentic RAG (Retrieval-Augmented Generation) solutions and multi-agent AI systems.
• Experience working with Large Language Models (LLMs) on Amazon Bedrock, including application development, model integration, and orchestration using AWS SDKs and related services.
• Proven experience building and maintaining CI/CD pipelines to support automated testing, continuous integration, and deployment of applications to Kubernetes-based environments.
• Familiarity with GitLab and GitLab CI/CD for source control management, automated builds, and deployment workflows.
• Experience with Helm charts, AWS CloudFormation, and infrastructure-as-code practices to enable scalable, repeatable, and seamless deployments to Amazon EKS environments.

Qualifications

• Extensive AWS experience, including services like Amazon EKS, Amazon Bedrock, Knowledge Bases, CloudWatch, AgentCore, Strands SDK, Auto Scaling Groups, Load Balancers, API Gateway, Lambda, Step Functions, AWS Glue, PostgreSQL, and Amazon RD.
• Experience with FastAPI-based applications and frontend/client integration.
• Experience with observability and FinOps tools, such as Langfuse and Phoenix.
• Experience designing and building Agentic RAG (Retrieval-Augmented Generation) solutions and multi-agent AI systems.
• Experience working with Large Language Models (LLMs) on Amazon Bedrock, including application development, model integration, and orchestration using AWS SDKs and related services.
• Proven experience building and maintaining CI/CD pipelines to support automated testing, continuous integration, and deployment of applications to Kubernetes-based environments.
• Familiarity with GitLab and GitLab CI/CD for source control management, automated builds, and deployment workflows.
• Experience with Helm charts, AWS CloudFormation, and infrastructure-as-code practices to enable scalable, repeatable, and seamless deployments to Amazon EKS environments.

Skills

• Practical development experience with Python 3.12+ and extensive AWS experience.
• Experience with FastAPI-based applications and frontend/client integration.
• Experience with observability and FinOps tools, such as Langfuse and Phoenix.
• Experience designing and building Agentic RAG (Retrieval-Augmented Generation) solutions and multi-agent AI systems.
• Experience working with Large Language Models (LLMs) on Amazon Bedrock, including application development, model integration, and orchestration using AWS SDKs and related services.
• Proven experience building and maintaining CI/CD pipelines to support automated testing, continuous integration, and deployment of applications to Kubernetes-based environments.
• Familiarity with GitLab and GitLab CI/CD for source control management, automated builds, and deployment workflows.
• Experience with Helm charts, AWS CloudFormation, and infrastructure-as-code practices to enable scalable, repeatable, and seamless deployments to Amazon EKS environments.

Benefits

• Competitive and generous employee benefits, including medical, dental and vision coverage, 401(k), life insurance, and other paid leave for qualifying circumstances.
• Eligibility for an incentive award.

Pay

Minimum Salary: $120,000
Maximum Salary: $175,000

Schedule

Full-time

Location

Whippany, NJ