At a Glance
- Tasks: Lead the development of cutting-edge AI/ML solutions and enhance the LLM Suite platform.
- Company: Join JPMorganChase, a leader in applied AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on learning and emerging technologies.
- Why this job: Shape the future of intelligent systems and make a real impact in tech.
- Qualifications: Degree in computer science or equivalent experience; strong Python skills required.
The predicted salary is between 80000 - 100000 € per year.
Build what’s next in applied AI at JPMorganChase - where your work shapes how teams use intelligent systems at scale. You’ll lead hands‑on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem‑solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you’ll thrive here. Join a team that values craft, security, and learning.
As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production‑grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high‑quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging‑technology events. You will explore and operationalize emerging patterns such as agent‑to‑agent communication, model context protocols, and agentic orchestration, turning early‑stage concepts into scalable, production‑ready capabilities.
Job Responsibilities
- Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges
- Write secure, high‑quality production code and maintain algorithms that integrate with existing systems
- Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery
- Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks
- Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock
- Identify hidden problems and patterns in data proactively to improve coding standards and system architecture
- Participate in software engineering communities of practice and events focused on emerging technologies
Required Qualifications, Capabilities, and Skills
- Computer science degree or equivalent practical experience
- Hands‑on experience with system design, application development, testing, and operational stability
- Proficiency in Python (FastAPI)
- Experience building microservices and APIs
- Experience with elastic compute, NoSQL databases, and messaging queues
- Strong understanding of the Software Development Life Cycle
- Solid grasp of CI/CD, application resiliency, and security
Preferred Qualifications, Capabilities, and Skills
- Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock
- Proficiency working with large language models and building agents with LangGraph
- Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages
- Experience with containerization
- Knowledge of agent‑to‑agent (A2A) communication concepts
- Familiarity with Model Context Protocol (MCP)
- Experience with agentic orchestrators, personal AI assistants, or AI skills development
Applied AI ML Lead - LLM Suite Engineering in London employer: Jpmorgan Chase & Co.
At JPMorganChase, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As an Applied AI ML Lead, you will not only engage in cutting-edge technology but also benefit from a supportive environment that prioritises professional growth and continuous learning. Our commitment to security, high-quality software, and community engagement ensures that you will thrive while making a meaningful impact in the world of applied AI.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI ML Lead - LLM Suite Engineering in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at JPMorganChase. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or projects that highlight your experience with AI/ML, make sure to share them. It’s a great way to demonstrate your hands-on engineering chops.
✨Tip Number 3
Prepare for technical interviews by brushing up on system design and coding challenges. Practice makes perfect, so get comfortable with Python and the tools mentioned in the job description.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're serious about joining the team.
We think you need these skills to ace Applied AI ML Lead - LLM Suite Engineering in London
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for applied AI and machine learning shine through. We want to see how excited you are about building intelligent systems and solving complex challenges. Share any personal projects or experiences that highlight your passion!
Tailor Your Experience:Make sure to customise your application to reflect the skills and experiences that align with the job description. Highlight your hands-on experience with Python, system design, and cloud services like Azure or AWS. We love seeing how your background fits into our vision!
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to describe your technical skills and achievements. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, FastAPI, and cloud services like Azure and AWS. Brush up on your knowledge of microservices, APIs, and the Software Development Life Cycle to show you can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex technical challenges. Think about how you turned ambiguity into reliable systems in past projects. This will demonstrate your hands-on engineering capabilities and your ability to think critically under pressure.
✨Emphasise Collaboration and Learning
Since this role involves working with talented builders, be ready to talk about your experiences in collaborative environments. Share how you’ve contributed to communities of practice or participated in tech events, as this shows you value teamwork and continuous learning.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on your knowledge of agentic systems, model context protocols, and coding standards. Practising coding problems or system design scenarios can help you feel more confident when faced with technical questions.
