AI Applications Developer

Job Description

Help shape how intelligent technology delivers real outcomes across the business. You will turn challenging problems into secure, scalable applications powered by artificial intelligence and advanced analytics. You will partner with experts across product, data, engineering, and governance to deliver solutions that matter. If you enjoy moving from concept to production and driving measurable impact, you will thrive here.

As an AI Applications Developer in the Intelligent applications team, you will design, build, and deliver production-grade solutions that apply model-driven capabilities to real business needs. You will partner with cross-functional teams to move from discovery through launch, with a focus on security, scalability, and responsible use. You will help improve reliability through systematic evaluation, monitoring, and iterative enhancement. You will contribute to shared patterns, documentation, and engineering practices that enable reuse and supportability.

 

Job responsibilities

• Design and deliver production-grade applications powered by large language models and advanced analytics
• Build agent-based systems that plan, decompose, and execute complex workflows across tools and services
• Develop and optimize prompts, evaluation methods, and guardrails to improve reliability and user outcomes
• Implement retrieval-augmented generation patterns to ground model outputs in trusted data sources
• Integrate applications with cloud services, data stores, and APIs to support end-to-end workflows
• Partner with product, data, engineering, and governance stakeholders to define requirements and deliver solutions
• Apply secure-by-design practices, including access controls, data protection, and auditability throughout development
• Create automated tests, monitoring, and observability to improve quality, safety, and operability in production
• Document architectures, decisions, and runbooks to enable supportability and reuse across teams
• Troubleshoot performance, latency, and model quality issues and deliver iterative improvements
• Stay current on advances in generative and agent-based approaches and translate them into practical solutions

 

Required qualifications, capabilities and skills

• Professional experience building and deploying modern applications in a production environment
• Hands-on Python development experience, including writing maintainable, testable code
• Demonstrated experience building intelligent applications using large language models, including prompt design and systematic evaluation
• Demonstrated experience implementing agent frameworks (for example, Google Agent Development Kit or similar)
• Demonstrated experience with retrieval-augmented generation solutions, including indexing, retrieval strategies, grounding, and citations
• Hands-on experience with containerized development and deployment (for example, Docker and orchestration platforms)
• Hands-on experience with cloud services for data and application workloads (for example, managed compute, storage, databases, and serverless services)
• Strong understanding of secure development practices, including identity and access controls and data handling principles
• Ability to translate ambiguous business problems into technical designs, milestones, and measurable outcomes
• Strong analytical and problem-solving skills, including root-cause analysis in production systems

 

Preferred qualifications, capabilities and skills

• Experience deploying and operating solutions on Kubernetes (for example, Amazon Elastic Kubernetes Service)
• Experience with managed model platforms and orchestration patterns (for example, Amazon Bedrock or similar)
• Experience building data pipelines and analytics workflows (for example, AWS Glue and Amazon Athena)
• Experience with relational database design and performance tuning (for example, Amazon Relational Database Service)
• Experience implementing model fine-tuning or adaptation techniques with clear evaluation and governance practices
• Experience partnering with risk, controls, privacy, and compliance stakeholders on model-enabled products
• Experience mentoring engineers and establishing team development standards and reusable patterns

About Us

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.

About the Team

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.