AI Senior Lead Infrastructure Engineer

Job responsibilities

• Lead the design and delivery of AI-enabled capabilities for Mainframe and Midrange systems management, focusing on intelligent automation that improves stability, efficiency, and operator experience.
• Translate the Advanced Capabilities Engineering tower strategy into executable technical plans, epics, and implementation roadmaps for assigned initiatives.
• Architect, build, and maintain agentic AI solutions that automate manual or repetitive infrastructure management tasks, ensuring solutions are secure, auditable, and production-grade.
• Own end-to-end engineering delivery for features/services you lead: requirements clarification, solution design, build, testing strategy, rollout, monitoring, and operational readiness.
• Partner with operations, SRE, architecture, risk, and control functions to ensure AI capabilities are implemented safely, transparently, and in alignment with JPMorganChase policies and regulatory expectations.
• Establish and follow strong engineering standards (design reviews, coding practices, CI/CD, documentation, observability, and incident readiness), and help uplift consistency across the team.
• Drive reliability outcomes by ensuring solutions meet resiliency, scalability, performance, and security objectives—enhancing service reliability and operational effectiveness without introducing unmanaged risk.
• Contribute to tooling strategy and vendor/product evaluations by prototyping, performing technical due diligence, and recommending fit-for-purpose approaches for Mainframe/Midrange automation.
• Provide clear technical communication to stakeholders: design rationale, tradeoffs, delivery status, risks/issues, and recommended mitigations.
• Mentor engineers through pairing, code/design reviews, and technical coaching; help build sustainable technical leadership depth within the organization.
• Champion JPMorganChase values, including a culture of inclusion, accountability, disciplined execution, and continuous improvement.

Required qualifications, capabilities, and skills

• 5+ years of hands-on software engineering experience delivering enterprise-grade systems (design, build, test, deploy, operate).
• Strong experience building automation platforms/services and integrating with infrastructure operations workflows; experience with AI-assisted automation and/or decision-driven systems is required.
• Experience designing and delivering production solutions with strong non-functional requirements (resiliency, scalability, performance, security, and operational excellence).
• Working knowledge of risk and control considerations in enterprise technology (e.g., SDLC controls, change management, access controls, auditability, data handling).
• Proven ability to lead technical delivery in a matrixed organization: influencing partners, unblocking execution, and driving outcomes across multiple teams/functions.
• Strong engineering fundamentals: API/service design, distributed systems concepts, data modeling, testing strategy, CI/CD, and observability (logs/metrics/traces).
• Experience mentoring and guiding other engineers via code reviews, design reviews, and technical feedback.

Preferred qualifications, capabilities, and skills

• Knowledge of Mainframe and Midrange automation, operational tooling, and platform management practices.
• Exposure to agentic AI patterns and controls (human-in-the-loop design, guardrails, prompt/tool governance, evaluation/monitoring) in production contexts.
• Track record partnering with SRE and operations teams on reliability engineering and operational efficiency improvements (e.g., toil reduction, incident automation, runbook modernization).
• Experience building integrations across heterogeneous infrastructure ecosystems (e.g., job schedulers, monitoring/alerting, ticketing workflows, configuration systems).
• Experience in financial services or similarly regulated industries, with understanding of governance, controls, and audit expectations.