Jersey City, NJ, United States
Open 4 months, first seen by us 120 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Develop generative AI, agent-based AI, and LLM solutions in Python from proof of concept to production
Lead semantic modeling strategy, ontologies, and governance
Build and govern a unified semantic layer for trusted analytics
Design context engineering approaches to improve model accuracy and latency
Build and maintain pipelines for model training, evaluation, monitoring, and operations
Develop generative AI, agent-based AI, and large language model solutions in Python from proof of concept through production deployment
Lead semantic modeling strategy, including ontology standards, governance, and lifecycle management aligned to enterprise needs
Build and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
Design context engineering approaches to improve model accuracy, latency, reliability, and overall performance in real-world workflows
Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and production operations
Required qualifications, capabilities and skills - Master’s degree in a data science-related discipline and 8 years of industry experience, or a PhD in a data science-related discipline - Hands-on experience developing and deploying machine learning and generative AI solutions using Python
Open 4 monthsWe first saw this posting 120 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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Day 120
Up longer than most. Similar jobs usually come down between day 4 and day 77.
Well past JPMorgan Chase’s usual: its jobs come down by about day 15.
From 51 similar postings that came down, and 1,000 of JPMorgan Chase’s. Coming down is not always a hire.
358 open jobs
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Job responsibilities - Develop generative AI, agent-based 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 in real-world workflows
- Master’s degree in a data science-related discipline and 8 years of industry experience, or a PhD in a data science-related discipline - Hands-on experience developing and deploying machine learning and generative AI solutions using Python - Demonstrated ability to write and maintain production-quality code, including reliability, performance, and maintainability considerations
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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
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We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
You will help shape how analytics and generative AI are delivered at enterprise scale—turning complex business problems into production-ready, measurable solutions. You will work with a collaborative team that values engineering excellence, responsible innovation, and continuous learning.
As an Applied AI and Machine Learning Lead at JPMorganChase within Corporate Technology Data Science and AI, you will design, build, and deploy scalable analytical and generative AI solutions that deliver measurable business value. You will partner with stakeholders to shape problem statements, define success metrics, and deliver production-ready models and intelligent workflows. You will help establish semantic modeling standards and a unified semantic layer that improves trust and consistency across analytics and AI use cases.
Job responsibilities
Required qualifications, capabilities and skills
Preferred qualifications, capabilities and skills
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Jersey City, NJ, United States
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