Software Engineer II

Help shape how teams across the firm build AI agents by contributing to a high-visibility AI Agent Platform. You will work on core building blocks—such as the software development kit (SDK), orchestration patterns, reusable components, and quality tooling—that enable teams to create conversational, voice, and document-extraction agent experiences. You will help turn complex problems into dependable production systems, raise engineering standards, and improve accuracy and reliability through disciplined evaluation and iteration.

As a Software Engineer II – AI Agent Platform at JPMorganChase within Enterprise Technology, you will contribute to the design and delivery of platform capabilities that enable large-language-model-powered agents at scale. You will collaborate closely with engineers, product partners, and risk and security stakeholders to ship measurable improvements in performance, developer experience, and operational stability. You will learn continuously, contribute ideas, and help set a high bar for quality in systems used by many teams and users.

Job responsibilities

- Build core SDK features and reusable components that enable teams to compose and operate AI agents consistently and safely.

- Implement orchestration and tool/function-calling patterns that improve reliability, traceability, and developer experience.

- Develop retrieval and grounding capabilities that connect agents to approved data sources and reduce incorrect or unsupported responses.

- Create evaluation datasets, benchmarks, and quality metrics to measure capability accuracy and guide iterative improvements.

- Add testing, observability, and monitoring features (tracing, logs, latency and cost metrics) to improve operability and incident readiness.

- Partner with cross-functional stakeholders to translate requirements into secure, scalable, production-ready solutions.

- Contribute to documentation, examples, and reference implementations that accelerate adoption and consistent usage.

- Participate in code reviews and design discussions to improve maintainability, performance, and overall engineering standards.

Required qualifications, capabilities and skills

- Formal training or certification on software engineering concepts and 2+ years applied experience

- Two or more years of hands-on Python development experience delivering production software.

- Experience building and operating backend services or platform components with attention to reliability, performance, and maintainability.

- Experience writing automated tests and using version control and code review practices to maintain quality.

- Experience integrating application components with data sources and building robust error-handling and observability practices.

- Ability to break down ambiguous problems into clear deliverables, iterate quickly, and communicate trade-offs to partners.

- Strong collaboration and communication skills, with a focus on outcomes and continuous improvement.

Preferred qualifications, capabilities and skills

- Experience building with large language model (LLM) application patterns, such as retrieval-augmented generation and prompt iteration.

- Familiarity with evaluation approaches for LLM-enabled systems (offline evaluation, regression testing, and metric-driven iteration).

- Exposure to voice or speech-enabled experiences (speech-to-text, text-to-speech, or streaming interactions).

- Exposure to document processing approaches (for example, optical character recognition and structured field extraction).

- Experience with containerization and continuous integration/continuous delivery practices.

- Familiarity with cloud platforms (for example, Amazon Web Services) and modern production operations practices.