[Hiring] Senior Platform Engineer @Axiomatic_AI

Role Description

As a Senior Platform Engineer at Axiomatic, you will own the reliability, deployment, and operational excellence of our AI platform. This role focuses primarily on infrastructure, CI/CD, and operations, with additional responsibilities for automation and tooling development.

• Lead deployment strategies and CI/CD pipelines across multiple environments
• Architect and maintain multi-cloud infrastructure (Azure, AWS, GCP) and on-premise deployments
• Own infrastructure as code using Terraform to automate provisioning and configuration
• Build comprehensive observability systems: monitoring, metrics, logging, and alerting
• Implement security controls, compliance frameworks, and data governance policies
• Develop automation tools, APIs, and scripts (Python) to improve operational efficiency
• Ensure system reliability, performance, and scalability
• Drive incident response, postmortems, and continuous improvement
• Troubleshoot infrastructure and application issues across multiple environments

Qualifications

• 7+ years of experience in Platform Engineering, Site Reliability Engineering, DevOps, or Infrastructure Engineering roles
• Deployment expert: Deep experience with CI/CD pipelines, release strategies, and production deployments at scale
• Multi-cloud expertise: Hands-on experience with Azure and AWS required (GCP is a plus)
• On-premise deployment experience: Linux system administration, bare-metal provisioning, networking
• Terraform expert: Deep experience writing and maintaining infrastructure as code
• Observability systems: Proven track record building monitoring, alerting, and metrics platforms
• Security mindset: Experience implementing security controls and best practices. Security certification preferred (CISSP, CEH, AWS/Azure Security Specialty, or similar)
• Data governance: Understanding of data privacy, residency requirements, and governance frameworks
• Backend/scripting skills: Python (preferred) or Go for automation, tooling, and operational scripts
• Kubernetes and container orchestration in production
• Strong Linux/Unix administration and scripting (Bash, Python)
• CI/CD platforms: GitHub Actions, GitLab CI, Jenkins, or similar
• Version control and GitOps practices
• Strong problem-solving and debugging skills
• Fluent in English (Spanish is a plus)

Requirements

• Design and implement deployment pipelines for multi-environment releases (dev, staging, production)
• Own the full deployment lifecycle: build, test, release, and rollback strategies
• Implement blue-green deployments, canary releases, and progressive rollouts
• Build automated deployment tooling and workflows
• Ensure zero-downtime deployments and rollback capabilities
• Optimize build and deployment performance
• Manage artifact repositories and container registries
• Design and operate multi-cloud infrastructure across Azure, AWS, and GCP
• Architect and deploy on-premise solutions for enterprise customers (Linux-based)
• Manage Kubernetes clusters, container orchestration, and networking
• Implement disaster recovery, backup strategies, and business continuity
• Optimize cloud costs and resource utilization
• Define and track SLIs, SLOs, and error budgets for critical services
• Write and maintain Terraform modules for infrastructure provisioning
• Implement GitOps workflows for infrastructure changes
• Automate infrastructure scaling, updates, and operations
• Ensure reproducible and version-controlled infrastructure
• Design comprehensive monitoring, logging, and alerting (Prometheus, Grafana, Datadog, or similar)
• Build dashboards for system health, performance, and business metrics
• Implement distributed tracing for microservices
• Conduct capacity planning and performance analysis
• Drive reliability improvements through data-driven insights
• Implement security best practices: identity management, secrets management, network policies
• Work towards or maintain security certifications (SOC 2, ISO 27001, or similar)
• Conduct security audits and vulnerability remediation
• Implement data governance policies for AI pipelines and user data
• Ensure compliance with data privacy regulations (GDPR, CCPA)
• Write automation scripts and tools in Python for operational tasks
• Build internal tooling for deployments, monitoring, and incident response
• Develop runbooks, automation, and self-healing systems
• Create APIs for infrastructure operations when needed
• Maintain high code quality and testing standards for tooling
• Participate in on-call rotation and lead incident response
• Conduct blameless postmortems and drive action items
• Build and maintain incident response playbooks
• Improve system resilience and failure modes
• Partner with engineering teams on deployment strategies and architecture
• Work with security team on compliance and governance
• Mentor engineers on operational best practices
• Document systems, procedures, and runbooks

Benefits

• Opportunity to work on technology that drives innovation in AI for scientific and engineering applications
• Contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions
• Collaborate with a global team of engineers and AI specialists
• Work in a diverse, inclusive, and authentic workplace

Company Description

Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.