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.
• Drivecontinuous systems tuning and analysis, validate service performance, and ensure requirements are met through disciplined testing and evidence-based results.
• Lead and executeintegration testing, complex troubleshooting, andPOCs to evaluate new capabilities and methods for managing IBM Power infrastructure.
• Raise engineering standards throughautomation, 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) withIBM Power hardware and related products.
• Deep expertise in - AIX operating system maintenance, PowerVM / VIOS, Power Firmware, andHMC maintenance, GPFS maintenance, Systems management agents/tools maintenance and testing
• Advanced knowledge ofUnix shell scripting,Python, andAnsible 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 buildingAI-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 toAIOps (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).