AI Applications Developer
JPMorgan Chase
- Location
- Metro Manila, National Capital Region, Philippines
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 1,524 approvals (FY2023)
- Posted
- 11h ago
Skills
About this role
Help shape how intelligent technology delivers real outcomes across the business. In this role, you will turn challenging problems into secure, scalable applications powered by artificial intelligence and advanced analytics. You will work alongside experts across product, data, engineering, and governance to deliver solutions that matter. If you enjoy moving from concept to production and seeing measurable impact, you will thrive here. Join us as we build the next generation of intelligent capabilities. As an AI Applications Developer in the AI Solutions Team , you will design, build, and deliver intelligent applications that transform business needs into measurable outcomes. You will partner with cross-functional teams to integrate modern model-driven capabilities into our platforms, from discovery through production. You will help ensure our solutions are secure, scalable, and aligned to responsible and compliant use. You will continuously learn and apply emerging approaches to improve quality, speed, and impact.
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 responses 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 teams 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 (indexing, retrieval strategies, grounding, and citations) Hands-on experience with containerized development and deployment (for example, Docker and orchestration platforms) Hands-on experience with Amazon Web Services core services for data and application workloads (for example, managed compute, storage, databases, and serverless) 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 Amazon Bedrock or similar managed model platforms and orchestration patterns 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 Experience