Platform Engineer

• Build, operate, and maintain containerized platform services using Kubernetes and related orchestration technologies.
• Design, implement, and maintain CI/CD pipelines supporting automated build, test, and deployment across multiple development teams.
• Develop and manage infrastructure-as-code using tools such as Terraform and Ansible.
• Implement platform monitoring, logging, and observability solutions to ensure availability and performance.
• Apply security hardening, patching, and compliance controls across platform components.
• Support development team onboarding, troubleshooting, and continuous improvement of platform services.
• Participate in Agile ceremonies and coordinate platform enablers with cross-functional teams.

Senior Platform Engineer

• Design and build the next-generation bare metal deployment pipeline to achieve sub-60-second provisioning times
• Develop and maintain Vultr’s bare metal automation and management toolkit
• Implement automated firmware update workflows across the bare metal fleet using IPMI/BMC protocols
• Build and optimize kexec-based fast boot and provisioning flows to minimize deployment latency
• Integrate cloud-init and instance metadata service for bare metal, enabling consistent configuration across VM and BM products
• Develop Puppet and Ansible modules for bare metal server configuration and lifecycle management
• Architect and implement VPC networking for bare metal instances, including network attach and routing automation
• Collaborate with the Provisioning and Orchestration teams to unify OS image pipelines and ensure bare metal integrates cleanly with Vultr’s reservation and assignment systems

Platform Engineer – Bare Metal

• Manage, lead & mentor our Platform Engineers
• Design, build, manage and monitor the infrastructure of RoadRunner technology
• Collaborate with product and engineering managers to define technical roadmaps and help guide our technology north star
• Maintain current awareness of marketplace trends, both technical and process improvements

Platform Engineer Manager

• Define and execute the long-range vision and strategy for AI infrastructure and platform engineering
• Recruit, hire, develop, and retain a high-performing engineering organization
• Establish clear ownership, accountability, and performance expectations across all functional teams
• Build and sustain a high-performing 24/7 operations model
• Lead GPU FinOps governance — utilization optimization, tenant quota enforcement, and cost reduction
• Empower the Security SRE Lead to maintain a world-class security posture

Executive Director, AI Infrastructure – Platform Engineering

• Champion a "platform as a product" mindset, regularly gathering feedback from engineering teams and iterating to improve the developer experience
• Design, build and maintain scalable, reliable infrastructure on Google Cloud to support our growing product needs
• Collaborate closely with developers to streamline local and CI/CD workflows, and champion platform best practices
• Evolve our observability stack - ensuring teams have the monitoring, logging and alerting they need to move quickly and confidently
• Implement and maintain secure-by-default patterns for networking, secrets management, IAM, and workload isolation
• Accelerate and complete the adoption of infrastructure-as-code (IaC) and GitOps to achieve consistent and auditable infrastructure changes

Senior/Staff Platform Engineer

• Define and execute the enterprise data and analytics platform strategy
• Establish standards, guardrails, and reusable capabilities for data use
• Own the strategy and lifecycle of foundational analytical data products
• Lead a unified organization spanning data engineering and analytics platforms
• Own platform-level enablement of data governance, quality, and lineage
• Lead budget, vendor strategy, and platform investment decisions
• Develop bench strength, succession pipelines, and differentiated talent
• Partner with CIOs, business leaders, and enterprise stakeholders

Vice President – Data & Platform Engineering

• Collaborate with data platform architects to design and specify platform tooling, services, and integrations
• Build data lake and lake house architectures
• Build streaming data architectures to support data platform tooling and services
• Collaborate with software teams to integrate streaming and batch architectures with software products
• Collaborate with data scientists, analysts, and business stakeholders to MVP optimal solutions
• Collaborate with data governance teams and data platform architects to build governance into technical solutions
• Maintain systems and services that provide transparency and observability into our critical systems
• Implement and promote engineering and architectural patterns, perform code reviews, and collaborate in architectural reviews
• Collaborate with product team data engineers and architects to MVP data products, maintain data models, and promote data modeling best practice
• Provide technical leadership and mentorship to product and data engineers, guiding their growth and professional development and enabling their ability to use platform tooling and services
• Lead by example through hands-on contributions to designing, coding, and troubleshooting complex data systems
• Identify and address performance bottlenecks and optimization opportunities within data pipelines, databases, and processing frameworks
• Optimize data processing workflows to improve efficiency and reduce latency
• Lead efforts to diagnose and resolve data-related incidents in a timely manner
• Will participate in the grooming of stories
• Will be responsible for their own tasking towards the completion of stories
• Will mentor junior members of the team and guide junior members on best practice
• Will participate in design
• Will be responsible for the quality of their own code and will participate in code review of others product
• Will be responsible for integrating their own code with the team's DevOps plan and implementation

Data Platform Engineer

• Build, test, and deploy end-to-end AI & Analytics applications, connecting AI/ML model inferences to functional user interfaces
• Bridge standard web architecture with machine learning operations (MLOps), handling model deployment and data pipelines
• Work with development teams and product managers to create software solutions
• Design client-side and server-side architecture
• Build the front-end of applications through visually appealing, responsive designs
• Develop, manage, and optimize databases
• Write and consume effective REST Application Programming Interfaces (APIs), troubleshoot, debug, and upgrade software
• Investigate technical, operational, and reliability issues during development and implementation
• Build and integrate software tools that improve system reliability, observability, and scalability
• Support set up of development and production environments, including deployment-related activities
• Develop best practices and methodologies for provisioning, configuration management, monitoring, and troubleshooting
• Collaborate with delivery teams to define and track service level indicators, service level objectives, SLAs, and error budgets
• Create and recommend process improvements that increase stability, efficiency, and operational readiness
• Contribute to the ongoing improvement of operational processes for automated agent workflows

Platform Engineer jobs in Montana

See all jobs on JobTailor