Infrastructure Engineer

• Build and scale distributed training infrastructure supporting large AI models across large GPU clusters.
• Design and improve systems that increase training reliability, efficiency, and resource utilization.
• Develop solutions for fault tolerance, checkpointing, recovery, and large-scale training operations.
• Integrate AI models into production training pipelines in partnership with platform, orchestration, and performance engineering teams.
• Diagnose and resolve issues impacting training throughput, stability, reliability, and cost efficiency.
• Build tools and automation that improve the developer experience for AI researchers and engineers.
• Establish best practices for training infrastructure, operational processes, and platform reliability.
• Contribute to the evolution of the AI infrastructure platform as an early member of the engineering team.

AI Training Infrastructure Engineer

• Architect, deploy, and operate Kubernetes clusters across AWS and Lambda's bare-metal datacenters.
• Build and maintain automation for cluster lifecycle management — provisioning, upgrades, and scaling.
• Own the reliability, performance, and security of Kubernetes workloads in production.
• Implement observability, logging, and alerting for clusters and critical workloads.
• Partner with product teams to design scalable, cloud-native services and CI/CD pipelines.
• Set the standards for resource management, networking, and RBAC across the platform.
• Lead incident response, root-cause analysis, and post-mortems for platform issues.
• Mentor engineers and raise the bar for platform engineering across the org.

Senior Platform Engineer – Core Infrastructure

• Provide hands-on leadership for Azure-based infrastructure, platform engineering, and DevOps capabilities supporting mission-critical financial systems.
• Architect, build, and operate secure, scalable, highly available Microsoft Azure environments for regulated workloads.
• Lead Platform Engineering practices including CI/CD pipelines, IaC, automation, observability, and SRE.
• Own operational execution for SOC 2 Type II and ISO 27001:2022 (evidence, remediation, audit readiness, continual improvement).
• Embed security and compliance controls into SAFe Agile delivery, PI planning, and release execution.
• Participate in architectural reviews and technical design decisions to ensure high-quality outcomes.
• Lead Microsoft Entra ID & Office 365 administration including identity governance, access controls, licensing, and security configuration.
• Produce reporting on infrastructure, security, and O365 expenses, trends, and cost-optimization opportunities.
• Evaluate infrastructure, security, and SaaS usage to drive measurable cost reduction.
• Lead all POD people-management responsibilities (hiring, onboarding, coaching, performance management, corrective action).
• Manage Release Management to ensure controlled, auditable, compliant deployments.
• Audit, maintain, and reconcile software/hardware inventory, licensing, subscriptions, and associated costs, identifying discrepancies and inefficiencies.
• Partner with Product, Security, Compliance, Audit, and IT Operations teams.
• Identify operational, security, and delivery risks and remove blockers to ensure predictability.
• Maintain visibility into platform health, delivery metrics, security posture, and compliance status.
• Participate hands-on in internal and external audits (ISO, SOX) including evidence prep, control validation, auditor Q&A, and remediation using tools like AuditBoard.

Infrastructure Engineering Team Lead

• Design, build, and operate the Kubernetes platform that powers GNI network automation, telemetry, and operations across data center, colocation, and cloud environments.
• Own the lifecycle management for GNI Kubernetes environments, including cluster onboarding, upgrades, capacity, availability, and recovery.
• Develop production-quality software and automation for cluster provisioning, validation, upgrades, remediation, and safe multi-cluster delivery through GitOps.
• Provide production support for network services hosted on the platform, working with Network Automation and service teams that retain ownership of application architecture, code, and features.
• Diagnose complex Kubernetes platform and hosted-service failures involving control-plane health, cluster networking, storage, scheduling, workload placement, and multi-cluster dependencies.
• Drive issues from initial signal through verified resolution.
• Define production-readiness and observability standards for the platform and hosted network services, including health signals, capacity, alerts, runbooks, and recovery.
• Participate in CFR’s production on-call rotation, including scheduled after-hours and weekend coverage.
• Lead incident response and recovery, then drive corrective actions to completion.

Senior Platform Engineer, Network Infrastructure

• Integrates DevSecOps tools as part of an agile team to achieve Continuous Integration and Continuous Deployment (CI/CD) applications.
• Represents the DevOps team for consistent messaging across all phases of complex development projects – including dependencies and blockers.
• Builds CI/CD solutions for large enterprises at an Individual Contributor level.
• Documents designs and changes to environments in Jira and/or Confluence as a record and to communicate information to other team members.
• Works on cross functional self-organizing teams as needed to collaborate in solving IT issues or implementing solutions to program requirements.
• Collaborates and communicates with management, internal, and outsourced development partners regarding all aspects of CI/CD and system.

Cloud Infrastructure Engineer

• Oversee technical strategy and architecture in ML Inference Platform services
• Design, implement, and scale critical engineering components and services to support ML inference and deployment
• Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services
• Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
• Provide technical direction that influences the entire company

Principal Software Engineer – Machine Learning Infrastructure

• Design, build, and operate cloud infrastructure across AWS and multi-cloud environments.
• Deploy and manage applications on Kubernetes (EKS and other environments), ensuring scalability, reliability, and performance.
• Build and maintain infrastructure-as-code using Terraform, enabling repeatable and auditable deployments.
• Develop and maintain CI/CD pipelines (e.g., CircleCI) to support rapid and reliable software delivery.
• Implement and operate observability systems (metrics, logs, tracing) to monitor system health and performance.
• Collaborate with backend and infrastructure teams to ensure services are designed for scalability, resilience, and operability.
• Support integration with edge-deployed systems, including handling synchronization, connectivity, and deployment workflows across distributed environments.
• Debug and resolve production issues across cloud infrastructure, networking, and application layers.
• Contribute to best practices around security, reliability, and performance across the platform.

• Lead the technical direction for Snap’s Service Infrastructure platform
• Design, build, and operate foundational backend infrastructure for Snap
• Act as a hands-on Staff-level tech lead driving complex technical initiatives
• Partner closely with engineers and leaders across infrastructure and product teams
• Improve the developer and operator experience for teams building on Snap’s backend platform
• Drive best practices in service reliability, observability, incident response, system performance, and cost efficiency
• Mentor and uplevel other engineers while resolving complex technical conflicts
• Help shape how Snap’s infrastructure evolves for an AI-first future

Staff Software Engineer, Core Infrastructure

• Lead the technical direction for Snap’s Service Infrastructure platform, defining multi-quarter and multi-year roadmaps across areas such as service mesh, compute, observability, and adjacent platform capabilities.
• Design, build, and operate foundational backend infrastructure that powers critical services across Snap with a focus on reliability, scalability, performance, and operational excellence.
• Act as a hands-on Staff-level tech lead, driving ambiguous and high-impact technical initiatives from concept through architecture, implementation, rollout, and iteration.
• Partner closely with engineers and leaders across infrastructure and product teams to align on technical direction, priorities, trade-offs, and long-term platform investments.
• Improve the developer and operator experience for teams building on Snap’s backend platform by creating durable systems, abstractions, and mechanisms that raise engineering velocity and quality at scale.
• Drive best practices in service reliability, observability, incident response, system performance, and cost efficiency across mission-critical infrastructure.

• Design and develop scalable, resilient offline indexing pipelines that process and transform data for Slack's search infrastructure.
• Partner with product engineering to conceptualize and ship new features for our large — and rapidly growing — user base.
• Ensure high availability and reliability across our distributed search systems through thoughtful collaboration and rigorous engineering.
• Drive significant business impact by contributing heavily to high-priority team projects.
• Take long-term ownership of team features and systems, proactively improving their health and the health of surrounding services.
• Deploy, configure, test, troubleshoot, maintain, and upgrade Solr clusters and environments.
• Continuously optimize Solr cluster infrastructure and configuration to sustain cluster health and search performance.
• Support our operations and customer-facing teams in triaging and resolving production issues efficiently.
• Conduct thorough, collaborative code reviews that raise the quality bar across the team.
• Champion improvements to engineering standards, tooling, and development processes.
• Build and ship production-grade software using modern engineering practices, with AI as a core pillar of your development workflow — leveraging AI tools to deliver secure, optimized, and high-quality code at speed.
• Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
• Contribute to building and maintaining a shared system context — an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
• Critically evaluate code (human- or AI-generated) for correctness, quality, security, and performance.

Staff/Sr. Software Engineer, Search Data Infrastructure

• Implement and support infrastructure technologies such as Microsoft Azure, VMware and networking technologies
• Execute migrations of on-premises platforms to cloud infrastructure
• Manage enterprise support requests from clients subscribing to Kraft Kennedy’s enterprise managed services
• Execute planned evening and weekend maintenance tasks in support of Kraft Kennedy’s enterprise managed services clients, when necessary
• Participate in weekly on-call rotation for evening and weekend support assistance, as requested by enterprise managed services clients
• Escalate to internal and, when necessary, external resources in an appropriate time frame to manage the resolution of complex client issues
• Provide on-site support, as necessary

Cloud Support Infrastructure Engineer

• Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
• Run and maintain test clusters used for system validation, diagnostics, and bring-up
• Validate firmware, drivers, and OS images across compute and GPU-enabled systems
• Support hardware qualification efforts for next-generation platforms
• Own GPU diagnostics and validation workflows across large-scale infrastructure
• Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
• Analyze system and GPU performance using tools such as NVIDIA DCGM
• Identify failure patterns and drive improvements in system stability and validation coverage
• Build and maintain automation for provisioning, validation, and system bring-up
• Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
• Improve the reliability, repeatability, and scalability of image pipelines and validation systems
• Manage and operate Linux-based systems in production and validation environments
• Manage virtualization technology
• Support bare-metal provisioning workflows, including PXE and image-based systems
• Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging
• Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
• Collaborate with platform and ML teams to ensure systems meet workload requirements
• Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

Infrastructure Engineer, GPU & Compute

• Own and evolve a scalable observability platform spanning metrics, logs, traces, and events
• Drive the productization of observability capabilities for both internal teams and external customers
• Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility
• Continuously improve observability systems to keep pace with rapid infrastructure buildouts
• Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish
• Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis
• Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar
• Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load
• Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams
• Build automated insights and enable proactive detection, forecasting, and system health visibility at scale
• Contribute to broader infrastructure engineering projects beyond observability
• Partner with infrastructure and platform teams to embed observability into core systems and workflows
• Support large-scale, distributed systems across compute, networking, and storage environments
• Work closely with customer-facing teams to deliver external observability experiences
• Collaborate with engineering, operations, and support teams to improve system transparency and reliability
• Help define best practices for observability across the organization

Infrastructure Engineer, Observability

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads
• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling
• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability
• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

Infrastructure Engineer, Storage

• At the direction of the Manager of Infrastructure Operations, design, build, and roll out new platforms and patterns to minimize incidents and enable customer facing and internal features.
• Deploy updates and improvements to support both Voltage Park’s internal and end customer use cases.
• Collaborate with colleagues in Infrastructure Engineering, Network Operations, Customer Success and Software and Platform Development Teams.
• Participate in the on-call rotation which is evenly distributed across all team members in a primary / secondary pattern where you are primary then move to a secondary position.

Infrastructure Operations Engineer

• Embrace Tanium’s mission and core values.
• Act as member of IT Infrastructure Engineering team with a focus on systems management and project delivery.
• Perform infrastructure deployment, management, planning, scaling, scheduling, etc.
• Drive and enhance automation wherever possible in the name of efficiency, scalability, and consistency.
• Work with a variety of key business groups to architect and implement technology and solutions.
• Be accountable for ensuring all technology is documented, deployed and configured securely and in alignment with best practices.
• Leverage AI and automation tools extensively for daily tasks, integrations and operation and management of IT and business services.
• Follow the change management process for system configuration, installations, and maintenance.
• Collaborate with other technical teams to resolve operational challenges and streamline workflows.
• Participate in projects related to Infrastructure, business execution, security, etc.
• Solve incidents and administrative tasks related to infrastructure services and other escalations from end-user support.
• Maintain comprehensive documentation of system configurations, processes, and procedures.
• Effectively communicate technical concepts and solutions to non-technical stakeholders, fostering a collaborative and productive working environment.
• Participate in on-call rotations.
• Be a team player who is adaptive, self-motivated, and solution-oriented.

IT Infrastructure Engineer

• Define the infrastructure integration strategy for scaling acquisitions securely
• Own and evolve the enterprise-wide M&A infrastructure integration strategy
• Serve as the senior technical lead for high-complexity integrations
• Lead large-scale transformation initiatives including security remediation
• Build and improve enterprise integration playbooks and tooling standards
• Drive strong partnerships across teams to align integration priorities
• Mentor and guide Infrastructure Engineers through architecture reviews

Principal Infrastructure Engineer – M&A

• Act as a core advisor for enterprise customers
• Design and integrate end-to-end data center Networking Fabrics
• Deliver resilient solution architectures for Kubernetes networking
• Architect high-availability application delivery networks
• Partner closely with field account teams and Systems Integrator partners
• Lead technical discovery sessions, architecture workshops, and proof-of-concepts
• Build, standardize, and share reusable reference architectures
• Stay current on industry trends and provide product feedback

Private Cloud Infrastructure Architect

• Define and own the long-term technical strategy for Bridge including Billing, IAM, Data, Operations, and Platform Infrastructure.
• Operate as a strategic partner to executive leadership, proactively identifying platform capabilities and constraints that shape product and business decisions.
• Anticipate infrastructure needs 12–18 months ahead of product demand, initiating foundational work before the business surfaces the requirement.
• Drive cross-functional initiatives to unlock new business models, pricing strategies, compliance requirements, and enterprise go-to-market motions.
• Establish Bridge platform as a durable competitive advantage through reliability, developer self-service, and enterprise flexibility.
• Architect and oversee development of scalable, highly available infrastructure spanning billing and subscription management, identity and access management, data pipelines, and core platform services.
• Lead technical decisions around build vs. buy, vendor selection, and platform integration strategies across all five domains.
• Ensure platform supports complex enterprise requirements including multi-seat licensing, usage-based billing, SSO/SAML/OIDC, granular policy hierarchies, and sophisticated financial reporting.
• Champion engineering excellence: API-first design, zero-trust security posture, microservices architecture, and cloud-native operational practices.
• Own end-to-end reliability, driving 99.9%+ uptime across billing-critical and identity-critical systems.
• Lead and grow a high-performing organization of 30+ engineers and managers across Billing, IAM, Data, Operations, and Platform Infrastructure.
• Foster a culture of technical excellence, psychological safety, and deep customer empathy across all Bridge teams.
• Mentor engineering managers and senior ICs, developing the next generation of technical leadership within the organization.
• Partner with Talent Acquisition to recruit top-tier engineering talent across a competitive market.
• Establish robust operational practices ensuring platform reliability, security, and compliance across all Bridge systems.
• Implement comprehensive monitoring, alerting, and incident response procedures, with clear SLAs and escalation paths.
• Drive compliance initiatives including SOX, PCI DSS, GDPR, and evolving international tax and data residency requirements.
• Define and track success metrics across all five domains, creating transparency with stakeholders and leadership.
• Collaborate with Product Management to translate business requirements into durable platform capabilities rather than one-off solutions.
• Work with Finance to ensure accurate revenue recognition, billing operations, and forecasting capabilities at scale.
• Partner with Sales and Customer Success to enable complex enterprise deal structures, custom contracts, and customer-specific billing requirements.
• Support Marketing and Growth teams with experimentation infrastructure for pricing, packaging, and conversion optimization.

VP, Infrastructure Engineering

• Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
• Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
• Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
• Improve reproducibility and reliability through dataset validation, monitoring, and testing
• Partner with ML engineers to support experimentation and model iteration
• Help optimize performance and efficiency across data processing and training systems
• Contribute to the evolution of our offline ML platform architecture as it scales

Infrastructure Engineer jobs in Washington

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AI Training Infrastructure Engineer

Senior Platform Engineer – Core Infrastructure

Infrastructure Engineering Team Lead

Senior Platform Engineer, Network Infrastructure

Cloud Infrastructure Engineer

Principal Software Engineer – Machine Learning Infrastructure

Cloud Infrastructure Engineer

Staff Software Engineer, Core Infrastructure

Staff Software Engineer, Core Infrastructure

Staff/Sr. Software Engineer, Search Data Infrastructure

Cloud Support Infrastructure Engineer

Infrastructure Engineer, GPU & Compute

Infrastructure Engineer, Observability

Infrastructure Engineer, Storage

Infrastructure Operations Engineer

IT Infrastructure Engineer

Principal Infrastructure Engineer – M&A

Private Cloud Infrastructure Architect

VP, Infrastructure Engineering

ML Infrastructure Engineer – Early Career/Internship