Shape the future of software development by building practical, generative artificial intelligence solutions that reach real users. Join a collaborative engineering team where you will learn modern delivery practices, grow your technical depth, and expand your career mobility. Bring your curiosity and builder mindset to help create reliable, secure capabilities that improve how teams work.
As an Applied AI ML Analyst at JP Morgan Chase, you will contribute to building, testing, and operating scalable generative artificial intelligence capabilities. You will partner with engineers and product partners to deliver production software components that support retrieval augmented generation and agent-based workflows. You will help improve reusable engineering components and standards to accelerate delivery across teams. You will support evaluation, monitoring, and operational readiness for deployed generative artificial intelligence systems.
Job Responsibilities
- Build software features and services that enable retrieval augmented generation experiences, including data ingestion, text segmentation, embedding generation, indexing, and retrieval.
- Implement agent-based workflow patterns, including planning and execution logic, tool integration, state management, retry handling, and error recovery.
- Contribute reusable engineering components by improving shared templates, software development kits, reference implementations, and developer documentation.
- Support evaluation and monitoring by helping create offline test sets, basic evaluation automation, telemetry dashboards, alerts, and regression checks integrated into deployment pipelines.
- Partner with agile teams to translate requirements into well-scoped technical tasks and participate in design reviews, code reviews, and testing.
- Operate delivered services by assisting with troubleshooting, debugging, and basic production support using logs and metrics.
- Apply secure engineering practices by following data handling controls, access permissions, and risk-aware deployment expectations.
- Promote a culture of inclusion, respect, and collaboration across teammates and stakeholders.
- 2+ years of software engineering and/or data engineering experience (including internships, cooperative education, or substantial academic projects).
- Experience writing production-quality code in Python, Java, or a similar programming language, including automated tests.
- Experience building or supporting end-to-end services or pipelines, such as application programming interfaces, batch processing, streaming processing, or data workflows.
- Familiarity with operating services in a team environment, including logging, debugging, and basic production support concepts.
- Hands-on exposure to generative artificial intelligence concepts through projects, internships, or work experience (for example retrieval augmented generation, prompt orchestration, embeddings and retrieval, or evaluation approaches).
- Understanding of core data engineering concepts such as data quality, schema changes, backfills, and idempotent processing.
- Awareness of data governance and personally identifiable information handling considerations.
- Familiarity with cloud fundamentals and modern engineering practices such as version control, build pipelines, and container basics.
- Demonstrated ability to communicate clearly and collaborate with engineers and partner teams.
- Bachelor’s or Master’s degree in Computer Science or equivalent practical experience.
- Familiarity with generative artificial intelligence orchestration frameworks and patterns for tool integration, retries, and safety guardrails.
- Coursework or project experience with machine learning frameworks such as PyTorch or TensorFlow.
- Exposure to evaluation automation for machine learning or generative artificial intelligence systems, such as test harnesses, offline metrics, or human review workflows.
- Exposure to Amazon Web Services deployment patterns, such as managed Kubernetes services, and basic cost and latency considerations.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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.
Skills Required
- 2+ years of software engineering and/or data engineering experience, including internships, cooperative education, or substantial academic projects.
- Production-quality programming experience in Python, Java, or a similar language, including automated testing.
- Experience building or supporting end-to-end services or pipelines, such as APIs, batch processing, streaming processing, or data workflows.
- Familiarity with service operations, logging, debugging, and basic production support.
- Hands-on exposure to generative AI concepts, such as retrieval-augmented generation, prompt orchestration, embeddings, retrieval, or evaluation.
- Understanding of data engineering concepts including data quality, schema changes, backfills, and idempotent processing.
- Awareness of data governance and personally identifiable information handling.
- Familiarity with cloud fundamentals, version control, build pipelines, and container basics.
- Clear communication and collaboration skills.
- Bachelor's or Master's degree in Computer Science or equivalent practical experience.
- Familiarity with generative AI orchestration frameworks and patterns for tool integration, retries, and safety guardrails.
- Coursework or project experience with PyTorch or TensorFlow.
- Exposure to evaluation automation for machine learning or generative AI systems.
- Exposure to Amazon Web Services deployment patterns, including managed Kubernetes services, and cost and latency considerations.
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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