AI Lab Infrastructure and Operations Manager

Job Summary:
Provides system operational support ensuring the effectiveness, efficiency, accuracy, and availability of systems for end users. Coaches and mentors less experienced team members.
Key Responsibilities:
Performs routine maintenance, facilitates customization and changes, and ensures system disaster recovery.
Leads new employee technology setup, including computer setup, delivery, and system access.
Resolves non-obvious issues and performs authorized changes and upgrades to existing systems.
Performs preventative maintenance on IT systems and networks, and monitors system performance and accuracy.
Conducts complex root-cause analysis to identify issues.
Coaches and mentors less experienced security analysts, and documents knowledge and solutions for use across the organization
Ensures IT services meet agreed performance, availability, and customer satisfaction standards by monitoring service metrics and proactively addressing issues impacting service quality.
Collaborates with Service Delivery Leaders and Engineering teams to validate fixes, confirm resolution, and implement preventive measures to avoid future service disruptions.
AI Lab Infrastructure & Operations Manager
Cummins AI Lab - Artificial Intelligence Laboratory
About Cummins AI Lab
The Cummins AI Lab integrates applied AI research, engineering workflows, manufacturing processes, and enterprise platforms to deliver high-value AI solutions across Cummins' global operations. We build and operate the infrastructure, technology ecosystem, and experimentation environment that enable rapid AI innovation, proof-of-concept validation, and scalable enterprise AI adoption.
Role Overview
The AI Lab Infrastructure & Operations Manager owns the reliable, secure, and efficient operation of the AI Lab environment. The role manages software platforms, AI services, hardware assets, computing resources, lab infrastructure, vendors, contractors, and supporting team members. It ensures that researchers, solution architects, and project teams can access fit-for-purpose platforms, tools, environments, and operational support.
This is a management and technical enablement role. The emphasis is on technology evaluation, introduction, governance, resource optimization, service continuity, and operational excellence rather than deep architecture design, platform engineering, or framework development.
Key Responsibilities1. Software Platform & AI Service Operations
Manage AI cloud environments, AI platforms, hosted AI services, model APIs, and related service subscriptions used by the AI Lab.
Coordinate the onboarding, configuration, operation, maintenance, and lifecycle management of AI services and platforms.
Evaluate and introduce external foundation models, model inference services, deployment frameworks, and technical tools based on lab needs.
Conduct fit-for-purpose technical assessments covering usability, compatibility, reliability, security, operational effort, scalability, and cost.
Maintain service inventories, ownership records, operating guidance, access models, and support processes for lab software capabilities.
Coordinate incident resolution, service changes, renewals, and escalation with internal IT teams and external providers.
2. Hardware Infrastructure & Computing Resource Management
Manage AI all-in-one servers, AI mobile workstations, GPU computing resources, lab devices, and related infrastructure assets.
Plan and coordinate resource allocation, workload scheduling, capacity usage, and computing availability across AI Lab activities.
Monitor utilization, availability, maintenance status, and operational risks, and recommend actions to improve effective resource use.
Own hardware inventory, assignment, maintenance coordination, upgrade planning, warranty tracking, and lifecycle management.
Coordinate equipment installation, configuration, technical support, and issue resolution with vendors, contractors, and enterprise IT teams.
3. AI Lab Environment, Network & Operational Governance
Lead day-to-day management and operations of the AI Lab infrastructure environment.
Coordinate lab environment readiness, network connectivity, access, accounts, permissions, storage, and supporting services.
Establish and maintain operating standards for resource requests, environment access, equipment usage, change management, incident handling, and asset governance.
Maintain operational documentation, service runbooks, inventories, usage records, and management dashboards.
Drive service continuity, issue prevention, operational risk management, and continuous improvement for lab infrastructure and services.
4. Data Security, Compliance & Risk Coordination
Coordinate data security, cybersecurity, privacy, and compliance requirements for AI Lab platforms, models, devices, networks, and external services.
Partner with enterprise IT, cybersecurity, architecture, procurement, legal, and relevant governance teams to complete required reviews and controls.
Support access control, data classification, secure configuration, logging, patching, vulnerability handling, and risk remediation processes.
Assess operational and security implications before introducing external models, cloud services, inference frameworks, or new devices.
Maintain risk, issue, exception, and remediation tracking for the lab infrastructure environment.
5. Technology Evaluation & Lab Enablement
Scan and evaluate emerging AI infrastructure technologies, AI services, model deployment options, inference frameworks, hardware solutions, and productivity tools.

Work arrangement
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