At a Glance
- Tasks: Lead a team to create innovative AI-driven software solutions and influence technical vision.
- Company: Join a forward-thinking tech company that values collaboration and innovation.
- Benefits: Enjoy competitive pay, health perks, remote work options, and career growth opportunities.
- Other info: Dynamic workplace with global collaboration and excellent career advancement potential.
- Why this job: Make a real impact with cutting-edge technology in a supportive, inclusive environment.
- Qualifications: Experience in software engineering and AI/ML, with strong leadership skills.
The predicted salary is between 72000 - 88000 £ per year.
Join us to make a meaningful impact as you lead a talented team in building advanced AI-driven software solutions.
You will have the opportunity to grow your career, collaborate globally, and influence the technical vision of our organization.
We value your expertise in software engineering and AI/ML, and offer a dynamic environment where your ideas and leadership drive real change.
Experience the benefits of working with cutting-edge technology and a supportive, inclusive team.
Together, we push the boundaries of what's possible.
As a Software Engineering Lead in our AI/ML Solutions Team, you will architect, design, and deliver secure, high-quality production software systems.
You will collaborate with product and business teams to set technical vision and execute strategic roadmaps for AI-driven solutions.
Your role involves translating business requirements into robust software and AI/ML specifications, ensuring timely delivery using Agile methodologies.
You will foster a culture of innovation, accountability, and engagement within a global organization.
Your leadership will help drive adoption of enterprise-authorized AI-assisted engineering practices and promote consistent validation standards across the team.
Job Responsibilities
- Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond conventional approaches.
- Develop secure, high-quality production code, review and debug code written by others.
- Lead a local team of software engineers and applied AI/ML practitioners, driving accountability and engagement.
- Collaborate with product and business teams to set technical vision and execute strategic roadmaps for AI-driven solutions.
- Translate business requirements into robust software and AI/ML specifications, define milestones, and ensure timely delivery using Agile methodologies.
- Architect, design, and develop secure, high-quality production software systems using Java or Python, integrating AI/ML techniques such as LLMs, Generative AI, and coding assistants.
- Identify opportunities to automate and remediate recurring issues, improving overall system reliability.
- Design experiments, implement algorithms, validate results, and productionize scalable and trustworthy AI/ML solutions.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
- Establish consistent validation standards, including secure coding, peer review, automated testing, and promote reuse of effective patterns.
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities.
Required Qualifications, Capabilities, and Skills
- Formal training or certification in software engineering concepts.
- Familiarity with agentic workflows and frameworks (e. g., Lang Chain, Lang Graph, Auto-GPT).
- Advanced proficiency in Java or Python for software system development; strong grasp of software engineering best practices, system design, application development, testing, and operational stability.
- Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals, and coding assistants.
- Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production-grade solutions.
- Demonstrated experience leading effective use of approved AI-assisted software development tools, 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.
- Good understanding of data structures, algorithms, and practical machine learning frameworks (e. g., Tensor Flow, Py Torch, Scikit-Learn).
- Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS).
- Hands-on practical experience delivering system design, application development, testing, and operational stability.
Preferred Qualifications, Capabilities, and Skills
- Experience working at code level with advanced AI/ML business applications (e. g., LLMs, Generative AI, NLP).
- AWS Certifications (Solution Architect Associate or Professional) are advantageous.
- In-depth knowledge of the financial services industry and their IT systems.
- Practical cloud native experience.
- #J-18808-Ljbffr
Lead Software Engineer - AI Engineering in London employer: JPMorgan Chase & Co.
JPMorgan Chase & Co. is an exceptional employer, offering a dynamic work environment in the heart of London’s International Private Bank. With a strong emphasis on professional development, employees benefit from comprehensive training programs and opportunities for career advancement, all while enjoying a collaborative culture that values teamwork and innovation. The role of Executive Assistant not only provides a chance to work closely with senior leaders but also allows for meaningful contributions to the success of the team in a prestigious financial institution.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - AI Engineering 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 JPMorgan Chase & Co. 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 JPMorgan Chase & Co..
✨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 JPMorgan Chase & Co..
✨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 JPMorgan Chase & Co. 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 - AI Engineering 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 JPMorgan Chase & Co..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at JPMorgan Chase & Co. 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 JPMorgan Chase & Co.
✨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 JPMorgan Chase & Co. 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.
