at J.P. Morgan
Bulge Bracket Investment BanksPosted 6 days ago
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**Senior Director of Software Engineering - Executive Director** Lead tech strategy, drive key programs, and innovate at a global financial giant. Guide multiple products and teams, deliver complex solutions, and champion firm culture. Expertise in cloud-native software (Java, Go, Python, Rust), AI-enabled development, and stable, secure systems required. Leverage cloud native experience and cloud technologies to scale operations and drive firm-wide objectives. Influence stakeholders and manage relationships across tech, product, and business units. Set portfolio-level standards, drive AI adoption, and ensure reuse and security. Proven software engineering experience in a relevant technical field and a Bachelor's degree or equivalent required.
- Compensation
- Not specified
- City
- London
- Country
- United Kingdom
Currency: Not specified
Full Job Description
Location: LONDON, United Kingdom
Were looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the worlds most influential companies.
As a Senior Principal Software Engineer at JPMorganChase within Infrastructure Platforms - Cloud Foundation Services, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances.
Job responsibilities
- Advises and leads on the strategy and development of multiple products, applications, and technologies across a portfolio
- Creates novel code solutions and drives the development of new production code capabilities across teams and functions
- Translates highly complex technical issues, trends, and approaches to leadership to drive the firms innovation and enable leaders to make strategic, well-informed decisions about technology advancements
- Drives adoption and implementation of technical methods in specialized fields in line with the latest product development methodologies
- Creates durable, reusable software frameworks that are leveraged across teams and functions
- Influences across business, product, and technology teams and successfully manages senior stakeholder relationships
- Champions the firms culture of diversity, opportunity, inclusion, and respect
- Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments
Required qualifications, capabilities, and skills
- Proven software engineering experience
- Practical experience delivering system design, application development, testing, and operational stability
- Expert in one or more programming language(s): Java, Go, Python, Rust, etc.
- Demonstrated prior experience with influencing across functions and teams and delivering value at scale
- Experience applying expertise and new methods to determine solutions for complex technology problems across various technical disciplines
- Extensive practical cloud native experience
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams
- Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies
- Strong experience with cloud-native architecture, event-driven architecture, test-driven development
- Domain-level expertise in building continuous compliance systems at scale in financial services
- Expert-level understanding and experience with regulatory and industry standards relating to technology controls in financial services
