Partner closely with product, operations, security, and controls stakeholders, and help drive design quality and operational excellence for production workloads.
As a Lead Software Engineer at JPMorgan Chase within Cloud Foundation Services, you will lead within the team and domain by owning features and services end-to-end, guiding designs for moderately complex initiatives, and setting expectations for engineering quality and operational rigor.
Job Responsibilities
- Lead the design and implementation of key components of a public cloud platform, primarily on AWS.
- Develop secure, high-quality production code and infrastructure automation (primarily in Python and Terraform), and review and debug code written by others to ensure correctness, performance, and maintainability.
- Influence product design, application functionality, and technical operations within the team and domain by proposing pragmatic architectures, tradeoffs, and standards aligned to firm SDLC, security, and controls expectations.
- Partner with operations, SRE, security, risk, and controls stakeholders to deliver compliant solutions, improve observability, reduce operational toil, and ensure audit-ready processes and artifacts.
- Drive automation and CI/CD improvements, including pipeline reliability, quality gates, testing strategy, and repeatable environment provisioning to support safe and fast delivery.
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.
- Use AI-assisted developer tools, including GitHub Copilot and Microsoft Copilot, to accelerate routine engineering tasks (for example, scaffolding, small utilities, repetitive patterns, test generation, refactoring suggestions, and first-pass documentation), while ensuring all outputs are validated and refined to meet production and security standards.
- Define and reinforce safe team usage patterns for AI-assisted development, including verification expectations (correctness, security implications, licensing/IP considerations, and compliance) and adherence to firm controls (for example, avoiding sensitive data in prompts and ensuring reviews and approvals occur before merge and release).
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- 4+ years of professional experience developing and designing software on AWS, with meaningful hands-on experience delivering solutions involving AWS database services and the infrastructure that supports them.
- Strong, practical proficiency in Python and Terraform, including building and maintaining production-grade automation and infrastructure as code.
- Advanced working knowledge of AWS services across traditional compute, containerized workloads, and serverless architectures, and how these patterns integrate with database services and platform guardrails.
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
- Working experience with engineering toolchains including Jira, Bitbucket, and Confluence, and day-to-day development in IntelliJ IDEA and Visual Studio Code.
- Practical experience with SQL and/or NoSQL concepts as applied to managed AWS database services (for example, data modeling, performance considerations, availability patterns, backup/restore approaches, and operational troubleshooting).
- Practical familiarity with AI-assisted coding tools, including GitHub Copilot and Microsoft Copilot, including effective prompting for engineering tasks and disciplined verification of outputs before use in any code or infrastructure configuration.
Clear understanding of responsible and approved AI tool usage, including adherence to firm controls, avoiding sensitive or confidential data in prompts, and applying engineering judgment to validate correctness, security posture, and compliance expectations.
Preferred Qualifications, Capabilities, and Skills
- Strong communication skills, including the ability to explain designs, risks, and operational tradeoffs to engineering peers and partner teams.
- Experience influencing decisions across adjacent teams within the domain (for example, platform consumers, SRE/ops partners, or security/control partners) through clear technical proposals and collaborative execution.
- Prior experience with Amazon RDS (e.g., RDS SQL Server, PostgreSQL) is preferred.
- Experience building reusable Terraform modules and standardized infrastructure patterns, including guardrails, policy-aligned defaults, and composable platform building blocks.
- Experience operating AWS database platforms at scale, including monitoring/alerting design, performance and capacity management, backup/restore validation, and availability/failover considerations.
- One AWS certification preferred (for example, Solutions Architect, Developer, or Data Engineer), and Terraform Certified Associate certification preferred.
- Demonstrated use of Copilot in team workflows to improve delivery outcomes (for example, accelerating test coverage, refactoring, documentation/runbook drafting), with a strong understanding of LLM limitations and risks (for example, hallucinations, security concerns, and licensing/IP considerations) and consistent verification practices.
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
High Risk Roles (HRR) are sensitive roles within the technology organization that require high assurance of the integrity of staff by virtue of 1) sensitive cybersecurity and technology functions they perform within systems or 2) information they receive regarding sensitive cybersecurity or technology matters. Users in these roles are subject to enhanced pre-hire screening which includes both criminal and credit background checks (as allowed by law). The enhanced screening will need to be successfully completed prior to commencing employment or assignment.
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