Applied AI ML and Context Engineer - Lead

JPMorgan Chase & Co. • Jersey City, NJ

9d

About The Position

Build what’s next in enterprise AI—solutions that materially improve how teams
make decisions, automate work, and serve internal customers. In this role, you
will take generative AI from concept to production and help set the standard for
semantic consistency across systems. You will partner closely with stakeholders
to turn complex business needs into measurable outcomes. You will mentor talent
and influence technical direction across Corporate Technology and supported
Corporate Functions. If you enjoy solving hard problems with real impact, this
is the opportunity.

As an Applied AI and Machine Learning Lead in the Corporate Technology Data
Science and AI team, you will design, build, and deploy scalable analytical and
generative AI solutions that deliver measurable business value. You will
collaborate with stakeholders to shape problem statements, define success
metrics, and deliver production-ready models and intelligent workflows. You will
help establish enterprise semantic modeling standards and a unified semantic
layer that improves trust and consistency across analytics and AI use cases. We
will support you with a collaborative environment where you can innovate, mentor
others, and continuously grow your skills.

Requirements

• Master’s degree in a data science-related discipline and 8 years of industry experience, or PhD in a data science-related discipline.
• Experience in data analysis, transformation, and analytics using Python.
• Demonstrated ability to develop and maintain production-quality code.
• Experience with continuous integration and unit test development.
• Strong written and verbal communication skills for technical and business audiences.
• Demonstrated scientific thinking and structured problem-solving skills.
• Ability to work independently and collaboratively in a team environment.
• Experience building and managing data pipelines and processing workflows.
• Track record of delivering actionable insights from data.
• Demonstrated attention to detail, curiosity, and ownership in complex analytical work.
• Commitment to continuous learning and professional growth in AI and machine learning.

Nice To Haves

• Familiarity with the financial services industry.
• Experience with A/B testing and data-driven product development.
• Knowledge of cloud-native deployment in large-scale distributed environments.
• Experience developing and debugging production-quality machine learning code.
• Exposure to prompt engineering practices for large language models.
• Exposure to orchestration libraries and frameworks for large language model applications.
• Experience implementing machine learning solutions in business environments.

Responsibilities

• Develop generative AI, agentic AI, and large language model solutions in Python from proof-of-concept through production deployment.
• Design context engineering approaches to improve model accuracy, latency, reliability, and overall performance.
• Lead enterprise semantic modeling strategy, including ontology standards, governance, and lifecycle management.
• Create scalable enterprise ontologies that model business entities, relationships, rules, and constraints in partnership with domain experts.
• Define semantic integration patterns across data pipelines, application programming interfaces, data contracts, and experience layers to resolve semantic conflicts.
• Build and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems.
• Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration methods.
• Build and maintain data pipelines and frameworks for model training, evaluation, optimization, and production operations.
• Implement responsible AI practices, model risk controls, and governance aligned to regulated environments.
• Communicate complex technical concepts clearly to technical and non-technical stakeholders, including senior leaders, to align outcomes to business objectives.
• Mentor engineers and data scientists and promote modern machine learning engineering best practices and continuous improvement.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees