At a Glance
- Tasks: Lead AI projects, mentor engineers, and develop innovative solutions for risk technology.
- Company: Join JPMorgan Chase, a leader in financial services with a focus on technology.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic work environment with excellent career advancement opportunities.
- Why this job: Make a real impact in AI while working with cutting-edge technologies and talented teams.
- Qualifications: Degree in Computer Science or related field; strong Python and data science skills required.
The predicted salary is between 70000 - 90000 £ per year.
As a Lead Software Engineer for AI – Vice President at JPMorgan Chase in Risk Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. You will leverage your expertise in software engineering, multi-agent system design, data science, and NLQ to deliver complex, high-impact initiatives. You will mentor and guide a team of engineers, foster best practices in AI engineering, and partner with data science, product, and business teams to deliver end-to-end solutions that drive value for the Risk business.
Job Responsibilities
- Lead the deployment and scaling of advanced generative AI and agentic AI solutions for the Risk business, with a focus on natural language querying of structured and unstructured data sources.
- Design and execute enterprise-wide, reusable AI frameworks and core infrastructure to accelerate AI solution development, including NLQ capabilities for diverse data types.
- Develop multi-agent systems for orchestration, agent-to-agent communication, memory, telemetry, guardrails, and NLQ-driven data retrieval and processing.
- Guide research on context and prompt engineering techniques to improve prompt-based model performance and NLQ accuracy, utilizing libraries such as LangGraph.
- Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring, and optimization at enterprise scale, with emphasis on NLQ workflows and orchestration.
- Build and maintain data pipelines and processing workflows for scalable, efficient consumption and querying of structured and unstructured data via natural language interfaces.
- Write secure, high-quality production code and conduct code reviews.
- Partner with Data Science, Product, and Business teams to identify requirements and develop NLQ-enabled solutions.
- Communicate technical concepts and results to both technical and non-technical stakeholders, including senior leadership.
- Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning.
Required Qualifications, Capabilities, And Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- Experience in data science and natural language querying, including experience deploying end-to-end pipelines on AWS.
- Strong proficiency in Python.
- Hands-on experience in system design, application development, testing, and operational stability.
- Experience using LangGraph for multi-agent orchestration and NLQ integration.
- Experience with AWS and infrastructure-as-code tools such as Terraform.
Preferred Qualifications, Capabilities, And Skills
- Strategic thinker with the ability to drive technical vision for business impact.
- Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows.
- Demonstrated leadership working with engineers, data scientists, and AI practitioners.
- Familiarity with MLOps practices and AI pipelines.
- Hands-on experience building and maintaining user interfaces for NLQ and data exploration.
Lead Software Engineer - AI for Risk Technology in London employer: Jpmorgan Chase & Co.
At JPMorgan Chase, we pride ourselves on being an exceptional employer, particularly for our Lead Software Engineer - AI role in Risk Technology. Our collaborative work culture fosters innovation and continuous learning, providing ample opportunities for professional growth while working on cutting-edge AI solutions that have a significant impact on the financial sector. With a commitment to mentorship and a focus on employee well-being, we offer a dynamic environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - AI for Risk Technology 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
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We think you need these skills to ace Lead Software Engineer - AI for Risk Technology 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.
