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- Tasks: Lead a talented team to develop cutting-edge AI solutions and drive innovation.
- Company: Join JPMorganChase, a leader in the financial industry with a focus on AI advancements.
- Benefits: Competitive salary, leadership opportunities, and a culture that values your vision.
- Other info: Mentor engineers and influence the direction of AI technology across the firm.
- Why this job: Shape the future of AI and make a lasting impact in a dynamic environment.
- Qualifications: PhD or deep experience in AI, strong communication skills, and team leadership.
The predicted salary is between 100000 - 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.
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.
AI Engineering Director employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
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, attend industry events, and engage with professionals on platforms like LinkedIn. We can’t underestimate the power of personal connections when it comes to landing that dream job.
✨Tip Number 2
Showcase your expertise! Create a portfolio or GitHub repository that highlights your projects and contributions in AI. This gives potential employers a tangible look at what you can bring to the table, and we all know actions speak louder than words.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in AI. We recommend practising common interview questions and scenarios related to AI engineering. Confidence is key, so let’s make sure you’re ready to impress!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search. Let’s get you on board and shaping the future of AI together!
We think you need these skills to ace AI Engineering Director
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the AI Engineering Director role. Highlight your leadership experience, technical expertise, and any relevant projects you've worked on. We want to see how you can contribute to our innovative team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your vision aligns with our goals at StudySmarter. Be sure to mention specific examples of your work that demonstrate your ability to lead and innovate.
Showcase Your Technical Skills: In your application, don't shy away from showcasing your technical prowess. Mention your experience with LLMs, cloud-native architectures, and any other relevant technologies. We love seeing candidates who can clearly articulate their technical capabilities!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be able to submit all your materials in one go. Plus, it helps us keep track of your application better!
How to prepare for a job interview at JPMorganChase
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs and agentic AI platforms. Be ready to discuss your hands-on experience with training and deploying models, as well as any innovative projects you've led. This is your chance to showcase your expertise and how it aligns with the company's goals.
✨Showcase Leadership Skills
As an AI Engineering Director, you'll be expected to lead a talented team. Prepare examples of how you've mentored engineers or influenced engineering direction in previous roles. Highlight your ability to foster an inclusive team culture and drive collaboration across business lines.
✨Communicate Clearly
You’ll need to convey complex technical concepts to diverse audiences, so practice explaining your ideas in simple terms. Think about how you can make your points compelling and relatable, especially when discussing advanced AI topics. Clear communication can set you apart from other candidates.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about system architecture, cloud-native platforms, and performance optimisation. Review key concepts like retrieval patterns, semantic search, and distributed computing. Being well-prepared will help you demonstrate your problem-solving skills and technical prowess.