At a Glance
- Tasks: Lead innovative AI projects and mentor a team of engineers in cutting-edge technology.
- Company: Join J.P. Morgan, a global leader in financial services with a focus on diversity.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Make a real impact in the world of finance through advanced AI and machine learning.
- Qualifications: Bachelor's or Master's in relevant fields and experience in Machine Learning Engineering.
- Other info: Dynamic environment with a commitment to diversity and inclusion.
The predicted salary is between 48000 - 72000 ÂŁ per year.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Machine Learning Engineer, Agentic AI within Risk Technology at JPMorgan Chase, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of software engineering, multi-agent system design and leadership to spearhead the delivery of complex and groundbreaking initiatives that will transform Asset and Wealth Management Risk.
You will be responsible for handsâon development, and leading and mentoring of a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce highâquality, scalable systems. You will also engage and partner with data science, product and business teams to deliver endâtoâend solutions that will drive value for the Risk business.
Responsibilities- Lead the deployment and scaling of advanced generative AI, Agentic AI and classical ML solutions for the Risk Business.
- Lead design and execution of enterpriseâwide reusable AI/ML frameworks and core infrastructure capabilities that will accelerate development of AI solutions.
- Develop multiâagent systems that provide capabilities for orchestration, agentâtoâagent communication, memory, telemetry, guardrails, etc.
- Conduct and guide research on context and prompt engineering techniques to improve the performance of promptâbased models, exploring and utilizing Agentic AI libraries like JPMC's SmartSDK and LangGraph.
- Develop and maintain tools and frameworks for promptâbased agent evaluation, monitoring and optimisation to ensure high reliability at enterprise scale.
- Build and maintain data pipelines and data processing workflows for scalable and efficient consumption of data.
- Develop secure, highâquality production code, and provide code reviews.
- Foster productive partnership with Data Science, Product and Business teams to identify requirements and develop solutions to meet business needs.
- Communicate effectively with both technical and nonâtechnical stakeholders, including senior leadership.
- Provide technical leadership, mentorship and guidance to junior engineers, promoting a culture of excellence, continuous learning, and professional growth.
- Bachelor's degree or Master's in Computer Science, Engineering, Data Science, or related field.
- Applied experience in Machine Learning Engineering.
- Strong proficiency in Python and experience deploying endâtoâend pipelines on AWS.
- Handsâon practical experience delivering system design, application development, testing, and operational stability.
- Handsâon experience using LangGraph or JPMC's SmartSDK for multiâagent orchestration.
- Experience with AWS and Infrastructureâasâcode tools like Terraform.
- Strategic thinker with the ability to drive technical vision for business impact.
- Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners.
- Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.
- Experience with Agentic telemetry and evaluation services.
- Demonstrated handsâon experience building and maintaining user interfaces.
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our firstâclass business in a firstâclass way approach to serving clients drives everything we do. We strive to build trusted, longâterm partnerships to help our clients achieve their business objectives.
We recognise that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mentalâhealth or physical disability needs.
Lead Software Engineer - Agentic AI/Machine Learning in London employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice đ€«
We think this is how you could land Lead Software Engineer - Agentic AI/Machine Learning in London
âšTip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A personal connection can often get your foot in the door faster than a CV.
âšTip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and machine learning. This gives potential employers a taste of what you can do.
âšTip Number 3
Prepare for interviews by practising common technical questions and scenarios. Donât forget to brush up on your leadership experiences, as theyâll want to see how you can guide a team.
âšTip Number 4
Apply through our website! Itâs the best way to ensure your application gets seen. Plus, it shows youâre genuinely interested in joining our team.
We think you need these skills to ace Lead Software Engineer - Agentic AI/Machine Learning in London
Some tips for your application đ«Ą
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Lead Software Engineer role. Highlight your expertise in Machine Learning, Python, and any relevant projects you've led or contributed to.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about this role and how your background makes you a perfect fit. Donât just repeat your CV; share stories that showcase your leadership and technical skills.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving multi-agent systems or AI frameworks, make sure to mention them. We love seeing practical examples of your work and how you've driven impact in previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at J.P. Morgan
âšKnow Your Tech Inside Out
Make sure youâre well-versed in the technologies mentioned in the job description, especially Python, AWS, and any specific tools like LangGraph or SmartSDK. Brush up on your knowledge of multi-agent systems and MLOps practices, as these will likely come up during technical discussions.
âšShowcase Your Leadership Skills
As a Lead Software Engineer, demonstrating your leadership experience is crucial. Prepare examples of how you've mentored junior engineers or led projects. Be ready to discuss how you foster collaboration between technical and non-technical teams, as this is key for the role.
âšPrepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and technical vision. Think about past challenges you've faced in ML engineering and how you approached them. Use the STAR method (Situation, Task, Action, Result) to structure your answers effectively.
âšCommunicate Clearly and Confidently
Effective communication is vital, especially when discussing complex topics with stakeholders. Practice explaining your projects and technical concepts in simple terms. This will show your ability to bridge the gap between technical and non-technical audiences, which is essential for this role.