At a Glance
- Tasks: Lead AI/ML initiatives to automate and optimise complex workflows in a dynamic banking environment.
- Company: Join J.P. Morgan, a global leader in financial services with a commitment to innovation.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Why this job: Shape the future of AI in finance and make a real impact on business operations.
- Qualifications: MSc/PhD in relevant fields and significant experience in AI application development.
- Other info: Mentorship opportunities and a focus on diversity and inclusion.
The predicted salary is between 72000 - 108000 £ per year.
As a Director of AI/ML within the Commercial and Investment Bank, you will set the vision and lead the enterprise portfolio for agentic AI that automates and optimizes complex business workflows at scale. You will guide cross-functional teams and strategic partners to define reference architectures and delivery roadmaps for multi-agent systems—leveraging LLMs, retrieval-augmented generation, and modern agent frameworks—while instituting governance, safety, and reliability standards and tracking measurable business outcomes.
Responsibilities
- Architect, develop, and productionize autonomous and assistive AI agents to streamline and enhance operations.
- Design multi-agent systems, including role definition, tool integration, planning, memory, and workflow orchestration using LangChain, CrewAI, AutoGen, ADK and LangGraph.
- Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search using vector databases such as Pinecone and Chroma, including indexing, retrieval policies, and evaluation.
- Build and integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing, error handling, and retries.
- Design and implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.
- Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.
- Deploy scalable AI services to cloud infrastructure, ensuring monitoring and observability for agent performance.
- Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics, and feedback loops to continuously improve reliability and utility.
- Partner with stakeholders to define requirements, design intuitive human-AI interfaces (voice, chat), and deliver measurable business impact.
- Analyze data to inform agent capabilities, optimize retrieval, and drive data-driven decision-making; and performance evaluations.
- Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices.
Required Qualifications
- MSc/PhD in Computer Science, Data Science, Machine Learning, or related field.
- Significant proven experience building and deploying AI applications in large scale production environments.
- Experience managing data science teams and coaching team members.
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
- Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).
- Experience with generative models (transformers, GANs/VAEs; diffusion models a plus).
- Strong understanding of data preprocessing, feature engineering, and evaluation techniques.
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Strong communication skills for both technical and non-technical audiences.
Preferred Qualifications
- Experience fine-tuning small language models (SLMs) with LoRA, QLoRA, DoRA; quantization and distillation a plus.
- Familiarity with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites.
- Experience with distributed computing, data sharding, and performance optimization.
- Hands-on with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration.
- Demonstrated experience in financial services, particularly investment banking operations.
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.
AI/ML Director employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Director
✨Network Like a Pro
Get out there and connect with folks in the AI/ML space! Attend meetups, webinars, or industry conferences. We all know that sometimes it’s not just what you know, but who you know that can help land that dream job.
✨Showcase Your Skills
Create a portfolio that highlights your projects and achievements in AI/ML. Whether it's GitHub repos or case studies, we want to see what you've done. This is your chance to shine and show potential employers what you're capable of!
✨Ace the Interview
Prepare for those tricky interview questions by practising your responses. We recommend doing mock interviews with friends or using online platforms. Remember, confidence is key, so show them you’re the right fit for the role!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. Let’s get you on board!
We think you need these skills to ace AI/ML Director
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your expertise in AI/ML, especially with frameworks like LangChain and CrewAI, to show us you're the perfect fit for the role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI/ML and how your vision aligns with our goals. Share examples of your past work that demonstrate your ability to lead cross-functional teams and deliver measurable business outcomes.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies! Make sure to mention your experience with Python, ML frameworks, and cloud platforms. We want to see how you can bring your hands-on experience to our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at JPMorganChase
✨Know Your Tech Inside Out
Make sure you’re well-versed in the AI/ML frameworks mentioned in the job description, like LangChain and CrewAI. Brush up on your Python skills and be ready to discuss your hands-on experience with these technologies during the interview.
✨Showcase Your Leadership Skills
As a Director, you'll need to guide teams effectively. Prepare examples of how you've managed data science teams in the past, focusing on mentoring and coaching. Highlight any successful projects where you led cross-functional teams to achieve measurable outcomes.
✨Prepare for Technical Questions
Expect deep technical questions about AI agents, RAG pipelines, and cloud deployment. Be ready to explain complex concepts in simple terms, as you’ll need to communicate with both technical and non-technical stakeholders.
✨Demonstrate Business Acumen
Understand how AI can drive business value, especially in investment banking. Be prepared to discuss how your previous work has impacted business outcomes and how you plan to align AI initiatives with the company’s strategic goals.