At a Glance
- Tasks: Lead a talented team to develop innovative AI solutions and drive industry advancements.
- Company: Join J.P. Morgan, a global leader in financial services with a commitment to diversity.
- Benefits: Competitive salary, growth opportunities, and a culture that values your vision.
- Other info: Dynamic environment with a focus on collaboration and inclusivity.
- Why this job: Shape the future of AI while mentoring the next generation of engineers.
- Qualifications: PhD or deep experience in AI, strong leadership skills, and exceptional communication.
The predicted salary is between 120000 - 150000 € per year.
Join us to shape the next generation of AI solutions and make a lasting impact on the industry. You will lead a talented team, collaborate across business lines, and drive innovation through advanced AI platforms. Your expertise will help us stay ahead in a rapidly evolving field, offering you opportunities for growth and leadership. At JPMorganChase, we value your vision and empower you to push the boundaries of what’s possible.
Job Summary
As an AI Engineering Director within LLM Suite engineering, AI/ML & Data Platforms team at JPMorganChase, you will lead a group of experts to develop horizontal capabilities through APIs, libraries, and thought leadership. You will collaborate with Line of Business AI teams to address priority use cases, design and build services, and promote best practices in AI. Your role involves mentoring AI engineers and ensuring we remain at the forefront of AI advancements. You will help shape our team culture and drive impactful solutions across the firm.
Job Responsibilities
- Lead the architecture and implementation of scalable, reliable LLM-based systems and agentic AI platforms for enterprise use cases.
- Design and build production-grade AI systems, including agents, harnesses, skills, memory architectures, guardrails, and tool‑use workflows.
- Architect and implement retrieval and context‑engineering patterns such as embeddings, semantic search, grounding, summarization, and prompt/version management.
- Engineer cloud‑native AI platforms on AWS using ECS, EKS, Lambda, SQS, SNS, containerized workloads, and DynamoDB‑backed distributed architectures.
- Optimize AI systems for latency, throughput, scalability, caching, context efficiency, and cost.
- Build APIs, integrations, MCP Servers, and reusable platform capabilities to connect AI systems with enterprise platforms, tools, and workflows.
- Establish evaluation, experimentation, regression, and observability frameworks to continuously improve AI system quality, reliability, and agent behavior.
- Mentor senior engineers and influence engineering direction through code reviews, architecture discussions, technical standards, and cross‑organizational leadership.
Required Qualifications, Capabilities, And Skills
- PhD or deep experience using LLMs and Agents to develop scalable applications, or experience in a top commercial AI research lab.
- Strong understanding of AI fundamentals and practical experience with data analysis and experimental design.
- Recent hands‑on experience training and deploying models and pipelines.
- Familiarity with distributed computing patterns for training, serving, and persistence of state.
- Experience building and leading high‑performing AI teams.
- Exceptional verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences.
- Ability to influence key decision makers with compelling technical arguments.
Preferred Qualifications, Capabilities, And Skills
- Experience with enterprise‑scale AI platform development.
- Knowledge of industry‑standard AI evaluation and observability frameworks.
- Expertise in cloud‑native architectures and container orchestration.
- Proven track record of cross‑functional collaboration and leadership.
- Familiarity with MCP protocols and enterprise integration patterns.
- Advanced skills in optimizing AI systems for performance and cost.
- Demonstrated commitment to fostering an inclusive and innovative team culture.
ABOUT US
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 first‑class business in a first‑class way approach to serving clients drives everything we do. We strive to build trusted, long‑term partnerships to help our clients achieve their business objectives. We recognize 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, color, 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 mental health or physical disability needs.
About The Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
AI Engineering Director employer: JPMorganChase
At JPMorgan Chase, we are committed to fostering a dynamic and inclusive work environment where innovation thrives. As an AI Engineering Director, you will not only lead a talented team but also have access to unparalleled growth opportunities within a global leader in financial services. Our culture prioritises collaboration and empowers you to push the boundaries of AI technology, ensuring that your contributions make a meaningful impact on the industry.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineering Director
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and agentic systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with cloud-native architectures and how you've led high-performing teams in the past.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our team at JPMorganChase.
We think you need these skills to ace AI Engineering Director
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI shine through! Share specific examples of projects or innovations you've been involved in that demonstrate your commitment to pushing the boundaries of AI technology.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter to highlight the skills and experiences that align with the AI Engineering Director role. Use keywords from the job description to show that you understand what we're looking for.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured documents that make it easy for us to see your qualifications and experience without wading through unnecessary fluff.
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!
How to prepare for a job interview at JPMorganChase
✨Know Your AI Fundamentals
Brush up on your understanding of AI fundamentals, especially around LLMs and agentic AI platforms. Be ready to discuss how you've applied these concepts in real-world scenarios, as this will show your depth of knowledge and practical experience.
✨Showcase Your Leadership Skills
Prepare examples that highlight your experience in leading high-performing AI teams. Discuss how you've mentored engineers and influenced engineering direction, as this aligns with the role's emphasis on leadership and team culture.
✨Demonstrate Technical Expertise
Be prepared to dive into technical discussions about cloud-native architectures and distributed computing patterns. Show how you've designed and built scalable AI systems, and be ready to explain your thought process behind architectural decisions.
✨Communicate Clearly and Effectively
Practice conveying complex technical concepts in a way that's easy to understand. This is crucial, as you'll need to influence key decision-makers. Use clear examples from your past experiences to illustrate your points during the interview.
