As a Lead Software Engineer, Vice President, at JPMorgan Chase within the Commercial and Investment Bank team, you are an integral part of an agile team that enhances, builds, and delivers trusted market-leading technology products in a secure, stable, and scalable way. In this senior team member contributor role, you will build a new AI-powered, promoter-based forecasting and planning platform for Corporate and Investment Bank (CIB) Finance to support forecasting, scenario analysis, and strategic planning. You will combine hands-on engineering with architecture-level decision making—promoting technical direction, making trade-offs, and anticipating future business needs—while consistently delivering secure, resilient, and scalable software solutions.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting to build an AI-first forecasting product and break down complex technical problems
- Develops secure, high-quality production code in Python and Java, and reviews and debugs code written by others
- Designs and implements LLM- and agent-based capabilities (e.g., tool use, workflow orchestration, evaluation/guardrails, prompt/version management) to power driver-based model building and scenario analysis
- Builds and evolves data and compute workflows on AWS and Databricks (batch + interactive), including data quality, lineage, and repeatable model runs
- Develops user-facing experiences using JavaScript/TypeScript and React to make complex forecasting workflows intuitive and auditable for Finance users
- Establishes architecture patterns for scalability, resiliency, and security; identifies and mitigates risks early (performance, data access, model behavior, explainability)
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve operational stability of applications and pipelines
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- 10+ years of software engineering experience delivering production systems (design, build, test, release, operate)
- Strong hands-on expertise in Python and/or Java with demonstrated delivery of secure, high-quality production code
- Strong experience building cloud-native solutions on AWS (compute, storage, security/IAM, networking, observability)
- Strong experience with LLMs and agentic systems, including orchestration patterns, tool/function calling, retrieval, structured outputs, evaluations, and safety/guardrails
- Experience building data-intensive applications and workflows using Databricks (Spark, Delta, jobs/workflows)
- Proficiency in JavaScript/TypeScript and React for building modern web applications
- Proficiency in automation and continuous delivery methods; strong SDLC discipline (CI/CD, testing, code quality, release controls)
- Advanced understanding of agile delivery, application resiliency, and secure engineering practices
- Strong system design skills with the ability to make pragmatic trade-offs and drive alignment across stakeholders
- Demonstrated strategic thinker: looks beyond immediate user requirements to anticipate future business needs and design extensible platforms
Preferred qualifications, capabilities, and skills
- Experience building AI platforms/products for non-technical users with emphasis on explainability, auditability, and reproducibility
- Experience with financial planning / forecasting platforms such as IBM TM1, Anaplan, or similar tooling and planning workflows
- Familiarity with driver-based planning, scenario analysis, and Finance planning & analysis processes
- Experience with modern analytics and dashboarding tools, including Sigma dashboards
- Experience with LLMOps practices (evaluation harnesses, prompt/version governance, monitoring/quality metrics)
- Experience with distributed systems and event-driven architectures