Salary: £61,000 - 101,000 per year
Requirements:
- Significant hands-on system/software development experience, delivering production services in secure, regulated environments.
- Demonstrated experience leading technical discussions, including technical direction, design reviews, quality standards, and operational readiness, across a team or program.
- Significant experience in at least one modern programming language: Java or Python.
- Experience using AI coding assistants such as GitHub Copilot or Claude Code to complete software engineering tasks.
- Solid understanding of building AI solutions using an LLM-backed architecture.
- Strong understanding of API design, microservices, and event-driven architectures.
- Experience building and operating cloud-native services on AWS, including Bedrock.
- Strong DevOps practices, including CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure as code (for example, Terraform or CloudFormation).
- Strong prompt engineering capability, including system prompts, few-shot prompting, tool/function calling, and structured outputs such as JSON schemas.
- Demonstrated experience driving secure and effective adoption of enterprise-approved AI-assisted engineering tools and setting team expectations for validating AI outputs for correctness, performance, and security.
- Financial services industry experience is preferred.
Responsibilities:
- Design and develop modular, maintainable AI systems and interfaces aligned to Infrastructure platform standards, optimizing for scalability, resiliency, and long-term operability.
- Partner closely with Applied AI/ML, Data Science, and Cybersecurity engineers to develop secure AI solutions for Infrastructure Platforms and our consumers.
- Create secure and high-quality production code, and review and debug code written by others.
- Evaluate AI solution approaches from an engineering standpoint to improve overall design quality, code quality, and operational outcomes.
- Influence peers and project decision makers to adopt leading-edge technologies where they create measurable value.
- Drive team adoption of enterprise AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes while establishing consistent validation standards, including secure coding, peer review, and automated testing.
- Promote reuse of effective patterns across the team.
- Contribute to the engineering community by advocating firmwide frameworks, tools, and practices for the AI-enabled System Development Life Cycle (SDLC).
- Foster a team culture of opportunity, inclusion, and respect.
- Mentor engineers and help ensure the organization stays at the forefront of AI engineering advancements.
Technologies:
- AI
- API
- AWS
- CI/CD
- Claude Code
- Cloud
- Copilot
- DevOps
- Docker
- GitHub
- JSON
- Java
- LLM
- Machine Learning
- Python
- Security
- Terraform
- microservices
- Marketing
More:
We are partnering directly with JPMorganChase to hire a Lead Software Engineer for Infrastructure Platforms Applied Artificial Intelligence and Machine Learning (AI/ML). This is a hands-on technical specialist role on a small, specialist team creating horizontal capabilities such as reusable APIs, libraries, reference architectures, and practical enablement to accelerate delivery across key products and platforms. We offer the opportunity to build new systems and capabilities that accelerate our business while working closely with engineering teams across the group to develop priority use cases, design and build services, and promote best practices for scalable, resilient, and secure AI adoption. Our team values inclusion, respect, and professional growth, and we are part of J.P. Morgans global financial services business and Corporate Functions organization.
last updated 40 week of 2026
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