At a Glance
- Tasks: Lead the development of innovative tools for engineers and operations, enhancing productivity and real-time monitoring.
- Company: Join a leading firm shaping strategic technology platforms used by thousands daily.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on technical ownership and innovative solutions.
- Why this job: Make a significant impact on engineering practices and operational efficiency in a dynamic environment.
- Qualifications: Strong Python skills, experience with AI tools, and a passion for developer tooling.
The predicted salary is between 80000 - 100000 £ per year.
Description
Join the ATRS Tools team and help shape the developer and operations experience on one of the firm's most strategic technology platforms, used by thousands of engineers and middle-office users every day.
Our remit spans two pillars: engineering productivity tooling that gives developers confidence in the changes they make, and operational tooling that gives the business real-time visibility and control over the platform.
The tools we build touch daily activity across the firm's front-to-back platform.
If you want your work to be visible across the organization and directly influence how a codebase of this scale is operated, tested, and evolved, this is the place.
As a Lead Software Engineer on ATRS Tools, you will design and build systems that give engineers confidence in the changes they make and give Operations users the real-time tooling they need to keep the business running.
You will partner across platform engineering, LOB teams, Controls, and Audit to deliver low-friction, high-impact platform capabilities.
Our culture values technical ownership, product thinking, and pragmatic delivery; we ship vertical slices, prove them end-to-end, then broaden.
- Job Responsibilities
- Build and evolve engineering productivity tooling: systems that help developers make changes with confidence, covering change management, regression and behaviour-comparison testing, and codebase health at scale
- Build and evolve operational tooling: real-time monitoring, alerting, and workflow frameworks that give Operations users the visibility and control they need to run the business
- Drive strategic platform initiatives that reshape how core capabilities, such as runtime configuration and large-scale codebase cleanup, are managed safely and deterministically across the estate
- Design and evolve real-time, event-driven systems built on modern streaming platforms that power operational monitoring and downstream consumers across lines of business
- Embed AI capabilities into team-owned products, surfacing intelligent recommendations, accelerating routine user actions, and turning ambiguous inputs into structured, reviewable outputs, using approved enterprise AI tooling
- Own features across their full lifecycle: discovery, design, implementation, rollout, telemetry, and operational support (including production incident response for team-owned components)
- Translate ambiguous asks from Operations teams, LOB engineers, and Controls partners into reusable platform capabilities, generalising per-team patterns into framework primitives adopted across the estate
- Partner with Controls and Audit stakeholders to implement effective, low-friction engineering controls in change management and release workflows
- Influence engineering standards and best practices across a broad developer community through RFCs, guidance, and reference implementations
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e. g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Strong software engineering fundamentals and a genuine passion for developer and operations tooling
- Proficiency in Python, with working knowledge of Type Script/React for web tooling and SQL for full-stack work
- Proficient user of enterprise-authorized AI-assisted development tools (coding, review, test acceleration, troubleshooting), with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use when building AI capabilities into products, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations, along with the ability to guide a team through these considerations
- Solid grounding in testing, reliability, and maintainable system design, comfortable with layered architectures, event-driven systems, and distributed state
- Ability to operate independently in ambiguous problem spaces (RFCs, greenfield platform initiatives) and collaborate effectively across teams
- Skill in turning loosely defined requirements into robust, widely adopted solutions: vertical slice first, broaden second
- Working knowledge of modern engineering workflows: testing, CI/CD, static analysis, version control, and deployment
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e. g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Preferred Qualifications, Capabilities, and Skills
- Experience building internal tools or platforms used by other engineers or operations users
- Familiarity with large or long-lived codebases and the challenges of maintaining them over time
- Experience with real-time or event-driven systems
- Experience with automated testing at scale, particularly for production-critical systems
- Experience integrating AI features into user-facing products
- Background in migrations, refactoring, or other platform-scale change initiatives
- Experience influencing engineering practices beyond your immediate team
Lead Software Engineer - Python / Athena Trade and Risk Services in London employer: JPMorganChase
JPMorganChase is an exceptional employer, offering a dynamic work environment in Greater London where innovation thrives. With a strong commitment to diversity and inclusion, employees benefit from collaborative agile teams, extensive professional development opportunities, and the chance to work on cutting-edge technology products that shape the future of finance. Join us to be part of a culture that values your contributions and supports your growth.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - Python / Athena Trade and Risk Services in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at JPMorganChase or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to JPMorganChase.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like JPMorganChase.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like JPMorganChase that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Lead Software Engineer - Python / Athena Trade and Risk Services in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at JPMorganChase.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at JPMorganChase and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at JPMorganChase
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If JPMorganChase uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
