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Lead Infrastructure Engineer – Infrastructure (IBM Power/AIX) with AI/Automation
lead · Technology / Software Development
Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies.
As a Lead Infrastructure Engineer at JPMorgan Chase within the Corporate Technology, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Technology Infrastructure organization builds and runs stable, resilient, and secure platforms at global scale. As a Power Infrastructure Engineer, you will help design, implement, and support highly available IBM Power platforms that underpin critical business services around the world. You’ll provide senior technical leadership across delivery, operational stability, integration testing, and proof-of-concepts (POCs) for next-level platform improvements. Continue to evolve your technical and cross-functional knowledge outside of your aligned domain of expertise.
Job responsibilities
- Design and deliver tailored IBM Power infrastructure solutions by translating requirements into resilient architectures and validated implementations.
- Install, configure, test, tune, and support IBM Power environments with a focus on robustness, performance, and operational excellence.
- Drive continuous systems tuning and analysis, validate service performance, and ensure requirements are met through disciplined testing and evidence-based results.
- Lead and execute integration testing, complex troubleshooting, and POCs to evaluate new capabilities and methods for managing IBM Power infrastructure.
- Raise engineering standards through automation, repeatable runbooks, and improved observability; mentor engineers and collaborate across roles to deliver shared outcomes.
- Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
- Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
- Works with other platforms to architect and implement changes required to resolve issues and modernize the organization and its technology processes
- Executes creative solutions for the design, development, and technical troubleshooting for problems of moderate complexity
- Strongly considers upstream/downstream data and systems or technical implications and advises on mitigation actions
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Deep knowledge of one or more areas of infrastructure engineering such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
- Senior hands-on experience providing technical expertise across the lifecycle (design, implementation, delivery) with IBM Power hardware and related products.
- Deep expertise in - AIX operating system maintenance, PowerVM / VIOS, Power Firmware, and HMC maintenance, GPFS maintenance, Systems management agents/tools maintenance and testing
- Advanced knowledge of Unix shell scripting, Python, and Ansible automation.
- Familiarity with open-source development models and tools for bug tracking and source control.
- Working knowledge of security-related technologies including system lockdown, cyber protection, and authentication/entitlement/encryption.
- Strong critical thinking, problem-solving, communication, and technical writing/documentation skills, with strong quality assurance and system/performance testing experience.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
- Ability to collaborate with different roles to achieve common goals; understanding of cloud, virtualization, APIs, and modern software languages.
- Experience building AI-assisted automation in Python (e.g., incident triage helpers, log/alert summarization, remediation suggestions, change-risk signals).
- Familiarity with GenAI/LLM application patterns such as RAG (retrieval-augmented generation) over operational knowledge (runbooks, known errors, standards), prompt design, evaluation, and guardrails.
- Practical understanding of MLOps / productionization concepts for AI features (CI/CD, versioning, monitoring, safe rollback), especially in regulated or security-sensitive environments.
- Data/telemetry skills relevant to AIOps (parsing logs/metrics/traces, anomaly detection concepts, improving alert precision through feedback loops).
- Security-aware AI development practices (data minimization, access control, secure-by-design patterns for AI integrations).