Lead Software Engineer- CIB Finance Technology

JPMorgan Chase & Co.•Jersey City, NJ

About The Position

As a Lead Software Engineer (VP) at JPMorganChase within Finance Technology, 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. This is a senior individual contributor role building a new AI-powered, driver-based forecasting and planning platform for CIB Finance to support forecasting, scenario analysis, and strategic planning. You will combine hands-on engineering with architecture-level decision making—driving technical direction, making trade-offs, and anticipating future business needs while delivering secure, stable, and scalable software.

Requirements

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

Nice To Haves

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

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