As a Lead Software Engineer at JPMorganChase within the Enterprise Technology, Infrastructure Platforms 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.
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problem.
- 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.
Own infrastructure capacity optimization solutions and build predictive/prescriptive models to identify capacity risk, performance bottlenecks, and right-sizing opportunities.
Design, develop, and productionize GenAI/agentic AI solutions for automation, decision support, and operational workflows, including LLM/SLM apps such as RAG and summarization/extraction.
Engineer production-grade backend services in Python/Java (REST APIs, microservices, reusable libraries) and own cloud-native data ingestion/processing pipelines for capacity analytics and AI use cases.
Build prompt engineering assets, routing strategies, and guardrails, and implement automated plus human-in-the-loop evaluation to improve quality.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Apply MLOps best practices across experimentation, versioning, CI/CD, deployment, monitoring, and lifecycle management; implement testing/benchmarking and observability; define success metrics/governance with stakeholders; and mentor engineers to uphold high standards.
Own and govern the end-to-end AI/ML optimization strategy—from architecture and engineering standards (quality, lifecycle, observability, secure SDLC) through cross-functional execution with SRE/platform/business—to deliver scalable automation, risk reduction, and measurable enterprise outcomes.
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Strong hands-on data engineering stack: Apache Spark (batch optimization, partitioning, shuffle tuning, reliability), Apache Airflow (DAG design, backfills, alerting, operational reliability, CI patterns), and Apache Iceberg (schema evolution, partition specs, snapshots, compaction).
- Proven applied AI/ML and GenAI delivery with measurable impact (RAG, extraction, summarization, ranking/classification, copilots, evaluation) and demonstrated ability to lead across teams and influence technical standards and execution.
- Deep distributed systems + production engineering expertise across APIs/microservices, CI/CD, observability, containers/Kubernetes, security, and reliability.
- Experience with MCP (Model Context Protocol), Agent Skills, and structured agentic architectures.
- Strong practical usage of AI engineering productivity tooling (for example, GitHub Copilot, Claude Code) in enterprise SDLC environments.
- Familiarity with VSI and Cloud Foundry contexts.
- Advanced Java engineering proficiency in addition to Python.
- Expert-level Python for production systems (packaging, dependency management, performance); strong Java proficiency is a plus.
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- 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
- Advanced proficiency in one or more programming languages (Python or Java)
- Demonstrated experience leading use of approved AI-assisted software development tools and setting validation standards
- Strong understanding of responsible AI use, data sensitivity, secure handling, and compliant adoption in engineering workflows
- Proficient in Software Development Life Cycle (SDLC) and production engineering best practices
- Strong hands-on data engineering: Apache Spark, Apache Airflow, Apache Iceberg
- Proven applied AI/ML and GenAI delivery (RAG, extraction, summarization, ranking, copilots, evaluation) with measurable impact
- Deep distributed systems and production engineering expertise across APIs/microservices, CI/CD, observability, containers/Kubernetes, security, and reliability
- Apply MLOps best practices across experimentation, versioning, CI/CD, deployment, monitoring, and lifecycle management
- Experience with MCP, Agent Skills, agentic architectures
- Practical usage of AI engineering productivity tooling (e.g., GitHub Copilot, Claude Code) in enterprise SDLC
- Familiarity with VSI and Cloud Foundry
- Advanced Java engineering proficiency in addition to Python
- Expert-level Python for production systems (packaging, dependency management, performance)
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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