Lead Software Engineer - Agentic AI, Java/Python

Lead Software Engineer - Agentic AI, Java/Python

Jersey City, NJ, United States and 1 more

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Job Information

Job Identification

210729666

Job Category

Software Engineering

Business Unit

Commercial & Investment Bank

Posting Date

09/10/2026, 02:03 PM

Locations

575 Washington Blvd, Jersey City, NJ, 07310, US

10 S Dearborn St, Chicago, IL, 60603, US

Job Schedule

Full time

Base Pay/Salary

Jersey City,NJ $156,750.00-$215,000.00

Chicago,IL $145,000.00-$185,000.00

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Commercial and Investment Bank's Engineering and Architecture Team, 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

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems

Develops secure high-quality production code, and reviews and debugs code written by others

Lead a local team of software engineers and applied AI/ML practitioners, driving accountability and engagement within a global organization.

Collaborate with product and business teams to set technical vision and execute strategic roadmaps for AI-driven software solutions.

Translate business requirements into robust software and AI/ML specifications, define milestones, and ensure timely delivery using Agile methodologies.

Architect, design, and develop secure, high-quality production software systems using Java or Python, integrating AI/ML techniques such as LLMs, Generative AI, and coding assistants

Identify opportunities to automate and remediate recurring issues, improving overall system reliability.

Design experiments, implement algorithms, validate results, and productionize performant, scalable, and trustworthy AI/ML solutions.

Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

Formal training or certification in software engineering concepts and 5+ years applied experience

Familiarity with agentic workflows and frameworks (e.g., LangChain, LangGraph, Auto-GPT)

Advanced proficiency in Java or Python for software system development; strong grasp of software engineering best practices, system design, application development, testing, and operational stability

Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals and coding assistants

Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production-grade solutions

Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security

Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn)

Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS)

Hands-on practical experience delivering system design, application development, testing, and operational stability

Preferred qualifications, capabilities, and skills

Experience working at code level with advanced AI/ML business applications (e.g., LLMs, Generative AI, NLP)

AWS Certifications (Solution Architect Associate or Professional) are advantageous

In-depth knowledge of the financial services industry and their IT systems

Practical cloud native experience

• Formal training in software engineering with 5+ years experience and advanced proficiency in Java or Python.
• Experience integrating AI/ML techniques (LLMs, Generative AI, NLP) and managing software/AI teams with hands-on production delivery.
• Proficiency in automation, CI/CD, cloud-native development (preferably AWS), and responsible AI use in secure engineering workflows.