As an Applied AI/ML Vice President within Global Private Bank, you will lead the design and build of agentic AI systems that execute reliable business workflows end-to-end. You will bring deep expertise in agent architectures—including memory, state, and context management; loop engineering; tool orchestration; and spec-driven development—to deliver safe, observable, and high-quality solutions. You will stay close to cutting-edge research, translating advances in LLMs, agent frameworks, reinforcement learning, knowledge graphs, retrieval, and self-improving systems into practical capabilities. You’ll thrive in a highly collaborative environment, partnering with business, technologists, and control partners to shape requirements, controls, and success metrics..
Job Responsibilities:
- Develop advanced agentic AI solutions across NLP, speech analytics, time series, reinforcement learning, and recommendation systems.
- Design robust agent architectures combining LLM reasoning with tools, structured data, and APIs—spanning state, memory, and context management, plus loop engineering (plan/act/observe, verification, termination, and fallback/escalation).
- Engineer reliable agent-driven workflows emphasizing correctness, traceability, and control-aware behavior (guardrails, approvals, auditable decision paths).
- Build knowledge-centric reasoning layers, including knowledge graphs and hybrid retrieval (RAG + graph + structured sources) to improve grounding and accuracy.
- Drive specification-driven development: author specs and contracts (schemas, validators, tool/skill interfaces) and build evaluation/regression harnesses.
- Advance agent quality via recursive self-improvement through automated evaluation and critique loops, red-team feedback, skill/prompt instruction optimization, and outcome-driven dataset curation (human-in-the-loop as needed).
- Coach and mentor AIML team members, setting a high bar for engineering rigor and research depth.
Required qualifications, capabilities, and skills:
- PhD in a quantitative discipline (e.g., CS/EE/Math/OR/Optimization/Data Science) or equivalent industry/research experience (e.g., 3+ years with PhD-equivalent depth; or MS with 5+ years).
- Demonstrated expertise building agentic AI systems, including several of: memory/state/context management, tool orchestration and workflow reliability patterns, loop engineering, spec-driven development, and prompt/skill instruction optimization.
- Strong hands-on experience with ML/DL methods and toolkits (e.g., PyTorch/TensorFlow plus core Python data/ML stack).
- Ability to design experiments and evaluation frameworks with metrics aligned to business outcomes (quality, reliability, latency, cost, safety).
- Experience with scalable data and model workflows (training and/or inference) and strong software engineering practices.
- strong communication skills to explain technical concepts to both technical and business audiences.
Preferred qualifications, capabilities, and skills:
- Knowledge in search/ranking, reinforcement learning, or meta-learning (especially for agent routing, policies, and self-improvement).
- Experience with knowledge graphs, entity resolution, and ontology design.
Experience with A/B experimentation and metric-driven product development; CI pipelines and unit/integration testing.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Master's or PhD in Computer Science, Statistics, Economics, Applied Math, Data Science, or a related quantitative field
- At least 5 years of hands-on ML experience in production environments with substantial focus on causal inference
- Deep expertise in causal inference methods (potential outcomes, propensity scores, IV, DiD, RDD, synthetic controls, doubly robust/double ML, uplift/heterogeneous treatment effect modeling)
- Experience designing and analyzing experiments (A/B tests, switchback, quasi-experiments) and reasoning from observational data
- Hands-on experience with LLMs and agentic AI (fine-tuning, RAG pipelines, prompt engineering, multi-step/tool-using agents) in production
- Strong Python skills and proficiency with causal libraries (DoWhy, EconML, CausalML), PyTorch, scikit-learn, and modern LLM/agent frameworks
- Experience with large-scale data processing technologies (Spark, Hive, SQL)
- Proven ability to communicate causal assumptions, limitations, and findings to non-technical stakeholders
- Financial services experience (wealth management, lending, or advisory)
- Experience with Bayesian/hierarchical modeling, structural causal models, sequential decision-making/contextual bandits
- Experience applying causal reasoning to LLM and agent evaluation (counterfactual eval, off-policy estimation, treatment-effect framing)
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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