What are the responsibilities and job description for the Python, Cloud - Lead Software Engineer position at JPMorgan Chase?
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As a Lead Software Engineer at JPMorgan Chase within the Chief Data and Analytics Office, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Execute creative software solutions, design, development, and technical troubleshooting for AI‑enabled applications.
- Develop secure, high‑quality production code; review and debug SDK and service integrations.
- Identify and automate remediation of recurring issues to improve reliability of AI features and services.
- Lead evaluation sessions with vendors and internal teams on model capabilities, safety, and integration patterns.
- Lead communities of practice to share prompt engineering, evaluation methods, and SDK best practices.
- Add to team culture of diversity, opportunity, inclusion, and respect.
- Build and ship AI‑powered features using AI (Bedrock, Foundry, Vertex AI), including prompt design, function calling, and SDK/REST integrations.
- Fine‑tune and deploy models; manage Model Registry and rollout across environments (online/batch inference).
- Implement input/output safety (guardrails, moderation) and comprehensive LLM usage logging/monitoring.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5 years applied experience.
- Hands‑on experience delivering system design, application development, testing, and operational stability for AI services.
- Advanced proficiency in Python software engineering skills
- Proficiency in automation and continuous delivery methods; strong unit/integration testing discipline.
- Proficient in all aspects of the Software Development Life Cycle and secure coding practices.
- Advanced understanding of CI/CD, application resiliency, and security for AI applications.
- Practical cloud‑native experience (GCP/AWS/Azure) and microservices/API design.
- Demonstrated experience with any of these AI platform (Bedrock, Foundry, Vertex AI) SDKs/REST APIs, prompt engineering, and model evaluation.
- DevOps: CI/CD pipelines, infrastructure as code, containerization/orchestration, observability, and cloud platforms.
Preferred qualifications, capabilities, and skills
- Terraform is a plus