Senior Director, Infrastructure -Infrastructure and Reliability

We are hiring a Senior Director of Infrastructure for our Product and Technology organization — a strategic leadership role accountable for designing, building and operating the cloud infrastructure that powers our platform, products and services. You will define infrastructure strategy and architecture, lead the transformation toward Infrastructure-as-Code and cloud-native operations, ensure reliability and security at scale, optimize costs, and build a team of infrastructure engineers who deliver operational excellence. You will partner closely with engineering teams, security, observability, performance engineering, and the product organization to ensure infrastructure enables rapid innovation while maintaining security, reliability and cost efficiency. 

Role overview 

As Senior Director of Infrastructure, you own the cloud platform, infrastructure architecture and operations that enable the entire company to build, ship and run software reliably and securely. You are accountable for infrastructure strategy, cloud architecture, deployment infrastructure, infrastructure security, observability infrastructure, disaster recovery, capacity planning and cost management across all production systems, development environments and support infrastructure. 

This is a strategic leadership role that combines deep technical expertise with broad organizational influence. You will establish infrastructure standards, drive adoption of cloud-native practices and Infrastructure-as-Code, build automation and self-service capabilities for engineering teams, ensure infrastructure meets security and compliance requirements, and drive cost optimization across cloud platforms. You work closely with engineering teams, security operations, observability, performance engineering, product leadership and cloud operations to ensure infrastructure is the reliable foundation upon which innovation happens. 

Your mandate is to transform infrastructure from a reactive, ticket-driven operation into a proactive, automated, self-service platform that enables engineering teams to deploy and operate systems independently while maintaining security, reliability and cost efficiency. Infrastructure is not separate from product development — it is a critical enabler. You will lead this transformation while building a high-performing team and delivering measurable improvements in deployment velocity, system reliability, security posture and cost efficiency. 

Duties and accountabilities 

Cloud platform and architecture strategy 

• Define organization-wide cloud strategy, platform architecture and infrastructure vision aligned with product strategy, scalability requirements and business goals. 

• Own multi-cloud strategy (if applicable): determine which workloads run on which platforms, manage vendor relationships, optimize for cost and capability. 

• Establish infrastructure standards, reference architectures and guardrails that make secure, scalable choices the easy choices for engineering teams. 

• Define infrastructure roadmap: prioritize platform improvements, deprecate legacy systems, and communicate progress to leadership and stakeholders. 

• Ensure infrastructure requirements are embedded in architecture reviews and design documents; make infrastructure-as-code mandatory for all services. 

Infrastructure-as-Code and automation 

• Lead adoption of Infrastructure-as-Code (IaC) practices across the organization; ensure all infrastructure is declarative, version-controlled and reproducible. 

• Own configuration management, infrastructure tooling and deployment pipelines; select and implement IaC tools (Terraform, CloudFormation, etc.) aligned with platform strategy. 

• Build self-service infrastructure capabilities: enable engineers to provision, configure and deploy infrastructure without infrastructure team bottleneck. 

• Automated disaster recovery, backup and recovery procedures; ensure infrastructure is resilient and recoverable. 

• Continuously improve automation and reduce manual operations; measure and reduce operational toil. 

Reliability, scalability and operations 

• Ensure infrastructure meets reliability, availability and scalability requirements; design systems that scale with customer demand. 

• Partner with observability team to instrument infrastructure for visibility; ensure all cloud resources, networks, databases and services are monitored. 

• Establish infrastructure SLOs and SLIs; maintain high availability and performance of platform services and shared infrastructure. 

• Capacity planning and forecasting; ensure infrastructure grows with demand, identify bottlenecks before they impact customers. 

• Lead incident response for infrastructure incidents; ensure rapid detection, diagnosis and remediation of infrastructure issues. 

Security and compliance infrastructure 

• Ensure infrastructure architecture meets security and compliance requirements (network segmentation, encryption, access control, audit logging). 

• Partner with security operations to implement infrastructure security controls: IAM policies, network security, secrets management, container security. 

• Maintain compliance infrastructure for regulatory requirements (SOC 2, ISO 27001, FedRAMP, GDPR, HIPAA, etc.); support audit and certification efforts. 

• Implement infrastructure for security operations: logging, monitoring, alerting, forensic investigation capabilities. 

• Manage cloud security posture; monitor and remediate security risks in cloud infrastructure (misconfigurations, exposed credentials, unauthorized access). 

Cost optimization and efficiency 

• Optimize cloud costs: analyze cloud spend, identify waste, negotiate vendor commitments, implement cost optimization strategies. 

• Partner with performance engineering on resource optimization; ensure infrastructure is efficient and no resources are wasted. 

• Implement cost allocation and chargeback mechanisms; make infrastructure costs visible to engineering teams and business units. 

• Drive infrastructure efficiency initiatives: rightsizing instances, optimizing database costs, managing data transfer costs, leveraging spot instances and reserved capacity. 

• Balance cost, performance and reliability; make informed trade-offs between different cloud options and resource configurations. 

Agentic AI infrastructure and emerging compute 

• Own infrastructure strategy for agentic AI workloads: GPU/ML compute infrastructure, inference serving, model storage and distribution. 

• Partner with AI/ML teams to design infrastructure for agent development, testing and deployment; manage inference serving infrastructure. 

• Optimize AI infrastructure costs: GPU utilization, batch processing, inference optimization, cost-per-inference efficiency. 

• Ensure AI infrastructure is observable and performant; integrate with observability platform for AI workload monitoring. 

Infrastructure culture and team leadership 

• Build and lead the infrastructure team, including cloud architects, DevOps engineers, database specialists, and infrastructure automation engineers. 

• Drive a culture of reliability, automation and operational excellence; make infrastructure work invisible and frictionless for engineering teams. 

• Mentor engineers and engineering leaders on infrastructure thinking; embed infrastructure expertise into product teams. 

• Communicate infrastructure strategy, wins and progress to engineering leadership, product leadership and executive stakeholders. 

What success looks like 

• Engineering teams can self-serve infrastructure: provision, configure and deploy systems without infrastructure team bottleneck or manual intervention. 

• All infrastructure is Infrastructure-as-Code, version-controlled and reproducible; no manual infrastructure configuration. 

• Deployment velocity improves; infrastructure is not a bottleneck to shipping features, and deployment frequency increases measurably. 

• System reliability improves; mean time to incident and mean time to recovery decrease, and uptime SLOs are consistently met. 

• Cloud costs are optimized and predictable; infrastructure spend per customer or per feature decreases over time without sacrificing reliability or performance. 

• Infrastructure is secure and compliant; compliance audits and certifications proceed smoothly, and security posture is strong. 

• AI infrastructure scales efficiently; agents deploy rapidly, inference latency meets targets, and cost per inference is optimized. 

• Engineering teams view infrastructure team as trusted partners and enablers, not as a bottleneck or overhead.

Department: Research and Development
Function: Engineering
Experience Level: Mid-Senior Level