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Senior Lead Software Engineer - Platform Engineering - Team Lead

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Fairygodboss
Full Time position
Listed on 2026-09-02
Job specializations:
  • Software Development
    Software Architect, Software Project Mgr/ Lead, DevOps, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 120000 - 180000 GBP Yearly GBP 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Job Description

Join us as we build products that solve real-world problems and put customers at the center of everything we do. You'll be part of a team that values collaboration, curiosity, and commitment, helping you realize your potential in an environment that nurtures skills and growth. We're people-first, and your leadership will be key to our success. At JPMorgan

Chase, you'll have the opportunity to shape the future of our platform and make a meaningful impact on the products and people around you.

As a Sr Manager of Software Engineering at JPMorgan

Chase within the Cloud Platform Engineering team, you will lead a high-performing squad focused on delivering scalable solutions that bring smart ideas to our customers. You will bridge the gap between technical strategy and business goals, cultivate engineering talent, and foster a culture of diversity, opportunity, inclusion, and respect. You will be responsible for the growth, health, and delivery of your engineering team, ensuring products are built to scale and aligned with our mission.

Job

responsibilities
  • Provide direction, oversight, and coaching for a team of software engineers, fostering an inclusive, high-performance culture
  • Oversee end-to-end delivery of platform initiatives, translating requirements into technical roadmaps and ensuring operational stability
  • Drive engineering standards and best practices, promoting high-quality code, robust release processes, and scalable infrastructure
  • Partner with senior leadership to set the long-term technical vision for the platform, aligning with business outcomes and regulatory requirements
  • Champion a "you-build-it-you-run-it" culture, overseeing incident response and identifying opportunities to automate remediation
  • Ensure successful collaboration across teams and stakeholders, driving consensus on architectural and delivery trade-offs
  • Identify and mitigate risks to execute a book of work, contributing to communities of practice and adoption of leading-edge technologies
  • Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and advanced applied experience. In addition, proven experience leading technologists to manage and solve complex technical items within your domain of expertise
  • Proven people-management or team-lead experience, with a track record of coaching engineers and driving team performance
  • Strong background in software engineering, including system design, cloud native systems, and Kubernetes
  • Ability to guide technical decisions and evaluate designs across complex, distributed systems
  • Experience managing complex technical delivery in an agile environment
  • Exceptional communication skills with the ability to influence both technical and non-technical stakeholders
  • Ability to translate business objectives into team-level tasks and priorities
  • Experience managing production systems, including incident response and reliability engineering
  • Experience leading multi‑team adoption of enterprise‑authorized AI‑assist ed development and delivery tools, including defining governance/ways of working (human‑in‑the‑loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns
Preferred qualifications,…
Position Requirements
10+ Years work experience
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