Business Operations
Running the business day-to-day, corporate strategy, and non-technical programme management. Covers business operations/BizOps, strategy & operations, chief of staff, non-technical programme/project management, business analysis (operational), workplace/office management, facilities, procurement, supply chain, construction, data center physical operations, manufacturing operations management, health/safety/environment (HSE/EHS), on-campus hospitality services, and executive support. This is for roles that keep the organisation running — NOT for technical roles that happen to have "operations" in the department name.
Roles
The canonical roles within Business Operations.
Program & Project Manager
Program & Project Managers at AI companies orchestrate complex, multi-workstream initiatives across distributed teams—translating priorities into delivery plans, managing dependencies across functions, and keeping cross-team execution on track. The day-to-day is universal program and project management: building and maintaining schedules and risk registers, running operating cadences and stakeholder reviews, removing blockers, and creating the documentation and SOPs that make programs reproducible. Scope varies widely—some PgMs run hardware and infrastructure programs, others run product launches, others run business or operational initiatives—but the canonical craft is the same. These managers typically sit within program management offices, engineering or operations leadership, or as embedded partners to specific functions, depending on company stage and how the function is organized.
Business Operations & Strategy Manager
Business Operations & Strategy Managers at AI companies translate executive priorities into operating processes and run the cadences—planning, forecasting, business reviews—that keep the company aligned. The day-to-day spans process design, cross-functional project leadership, data analysis and dashboarding, and acting as a connective layer between executive leadership and the teams executing against strategy. Specific scope varies by company stage and industry: at infrastructure-heavy businesses, work centers on capacity and cost; at AI software companies, it skews toward GTM efficiency and customer lifecycle economics; at vertical AI companies, it follows the underlying transaction model of the business. What is consistent is the operating-system role—building scalable processes, surfacing what is working and what is not, and giving executives clean signal to act on. These roles typically sit within strategy, BizOps, or chief-of-staff functions, partnering across finance, product, sales, and engineering.
Supply Chain & Procurement Manager
This role acts as the strategic commercial hub for AI infrastructure supply chains, negotiating with suppliers and managing vendor relationships to ensure critical components—from GPUs and servers to power and cooling systems—arrive reliably and cost-effectively. Unlike generalist procurement roles, specialists here partner closely with engineering teams to understand technical requirements and stay ahead of hardware trends, shaping sourcing strategies that directly impact data center deployment timelines and capital efficiency. The role sits within supply chain and procurement functions at rapidly scaling AI infrastructure companies, working cross-functionally with engineering, project management, and operations to translate infrastructure expansion plans into executable supplier relationships and long-term capacity commitments.
Construction Manager
Construction managers direct the complete build-out of AI data center infrastructure, overseeing site development, structural systems, MEP installation, and interior fit-out while coordinating multiple trades and managing schedules, budgets, and safety protocols. They distinguish themselves from general construction roles by specializing in mission-critical facilities where system reliability directly impacts AI compute uptime, requiring deep coordination with commissioning teams and operations handover. These professionals typically embed within dedicated infrastructure delivery teams at hyperscale AI companies, working alongside project engineers, cost controllers, and commissioning specialists to translate architectural designs into operational facilities that meet exacting performance and efficiency standards.
Executive Assistant
This role manages complex calendars, communications, and logistics for senior leaders at AI infrastructure and generative AI companies, ensuring executives operate at peak effectiveness in fast-paced, scaling environments. Unlike general administrative roles, Executive Assistants in AI firms navigate the unique demands of technical leadership—coordinating with engineering, product, and infrastructure teams while supporting high-stakes initiatives like board meetings, investor relations, and global GTM operations. These professionals typically report to a leadership support manager or work within a structured executive support function, partnering closely with C-suite and VP-level leaders to anticipate priorities, execute flawlessly, and drive operational excellence across distributed, multi-timezone organizations building the next generation of AI cloud infrastructure.
Data Center Operations Manager
This role leads day-to-day and strategic operations of mission-critical data center facilities supporting AI infrastructure, managing teams of technicians and overseeing mechanical, electrical, and cooling systems across one or multiple sites. It distinguishes itself from hands-on technician roles through its focus on regional or multi-site leadership, vendor management, preventive maintenance programs, and executive-level performance accountability for uptime and reliability. These managers sit within larger infrastructure operations teams at hyperscale AI cloud providers, partnering closely with hardware engineering, construction, and capacity planning functions to ensure facilities reliably support dense GPU and compute deployments at scale.
Workplace & Facilities Manager
Workplace Managers in AI companies own the day-to-day operational heartbeat of their offices, managing everything from facilities and vendors to employee experience and event logistics. They distinguish themselves through proactive problem-solving and a deep commitment to creating inclusive, high-functioning spaces that reflect company culture—going beyond reactive maintenance to shape how teams collaborate and innovate. These roles typically sit within operations or people functions, partnering closely with HR, finance, security, and leadership to ensure offices scale seamlessly alongside rapid growth while maintaining the welcoming, functional environments that fast-moving AI teams need to do their best work.
Manufacturing & Quality Manager
This role owns the quality and operational excellence of AI infrastructure manufacturing from raw material intake through final shipment. Managers in this position lead cross-functional teams spanning receiving inspection, production quality, and compliance, ensuring that modular data centers, power systems, and other mission-critical hardware consistently meet rigorous internal standards and regulatory requirements like ISO 9001 and UL certifications. They balance strategic quality systems design with hands-on oversight of inspection teams and technicians, driving continuous improvement through robust CAPA processes, calibration programs, and root cause analysis while partnering with engineering and supply chain to resolve design-to-build conflicts at scale.
Warehouse & Logistics Coordinator
This role coordinates the movement and tracking of specialized hardware components—servers, GPUs, and networking equipment—that power AI infrastructure deployments across global data centers and research labs. Unlike broader warehouse roles, this position focuses specifically on managing high-value, mission-critical assets for AI cloud platforms, requiring technical knowledge of data center hardware and familiarity with deployment timelines that directly impact AI model training and inference capabilities. Warehouse & Logistics Coordinators typically embed within fast-growing infrastructure teams at companies scaling AI compute capacity, working closely with data center operations, engineering labs, and external logistics partners to ensure seamless asset flow from procurement through deployment to eventual secure disposal.
Health, Safety & Environment Manager
This role oversees health, safety, and environmental programs across AI infrastructure operations, including data centers, manufacturing facilities, and autonomous vehicle testing sites. Professionals in this position develop and enforce HSE policies, conduct risk assessments and incident investigations, and ensure regulatory compliance with local and federal standards. They distinguish themselves through hands-on implementation of safety protocols and proactive hazard mitigation rather than purely advisory functions, often serving as the primary point of contact between operations teams, external regulators, and senior leadership. These roles typically embed within matrixed organizations that span facilities management, HR, legal, and operational teams, requiring strong cross-functional communication to build safety culture across distributed or rapidly scaling AI infrastructure.
Energy & Power Manager
Secures, procures, and manages power supply for AI compute infrastructure. Covers energy procurement and Power Purchase Agreements (PPAs), commercial energy development, power transaction management, load interconnection with utilities and grid operators, energy market analysis and forecasting, nuclear/renewable commercial development, and on-site/behind-the-meter generation strategy. Distinct from data center operations (which runs facilities day-to-day) and from sales (which sells software to energy companies) — the defining mandate is securing reliable, cost-effective, and increasingly clean power supply at the scale required by modern AI compute.
Recent Jobs
The latest Business Operations openings across the AI industry.