{"id":3848380,"url":"https://alion.io/job/axiomatic-senior-platform-engineer","title":"Senior Platform Engineer","company":{"id":3841554,"name":"Axiomatic","domain":"axiomatic.ai","url":"https://alion.io/company/axiomatic-3","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Singapore"],"countries":["SG"],"hiring_countries":["JP","SG"],"hiring_countries_total":2,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Blue-Green Deployment","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Incident Management","optional":false},{"name":"ISO 27001","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Self-Healing","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SOC 2","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Bash","optional":true},{"name":"FastAPI","optional":true},{"name":"FedRAMP","optional":true},{"name":"FinOps","optional":true},{"name":"GitHub Actions","optional":true},{"name":"GitLab CI","optional":true},{"name":"Go","optional":true},{"name":"HIPAA","optional":true},{"name":"Istio","optional":true},{"name":"Jenkins","optional":true},{"name":"Linkerd","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true},{"name":"Service Mesh","optional":true},{"name":"Unix","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-11-05T21:11:11Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T08:42:04Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About us:\nAxiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows. \nOur mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030. \nWe aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.\nPosition Overview\nAs 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.\nYou will:\nLead deployment strategies and CI/CD pipelines across multiple environments\nArchitect and maintain multi-cloud infrastructure (Azure, AWS, GCP) and on-premise deployments\nOwn infrastructure as code using Terraform to automate provisioning and configuration\nBuild comprehensive observability systems: monitoring, metrics, logging, and alerting\nImplement security controls, compliance frameworks, and data governance policies\nDevelop automation tools, APIs, and scripts (Python) to improve operational efficiency\nEnsure system reliability, performance, and scalability\nDrive incident response, postmortems, and continuous improvement\nTroubleshoot infrastructure and application issues across multiple environments.\nYour mission\nDeployment & CI/CD\nDesign and implement deployment pipelines for multi-environment releases (dev, staging, production)\nOwn the full deployment lifecycle: build, test, release, and rollback strategies\nImplement blue-green deployments, canary releases, and progressive rollouts\nBuild automated deployment tooling and workflows\nEnsure zero-downtime deployments and rollback capabilities\nOptimize build and deployment performance\nManage artifact repositories and container registries\nInfrastructure & Cloud Operations\nDesign and operate multi-cloud infrastructure across Azure, AWS, and GCP\nArchitect and deploy on-premise solutions for enterprise customers (Linux-based)\nManage Kubernetes clusters, container orchestration, and networking\nImplement disaster recovery, backup strategies, and business continuity\nOptimize cloud costs and resource utilization\nDefine and track SLIs, SLOs, and error budgets for critical services\nInfrastructure as Code\nWrite and maintain Terraform modules for infrastructure provisioning\nImplement GitOps workflows for infrastructure changes\nAutomate infrastructure scaling, updates, and operations\nEnsure reproducible and version-controlled infrastructure\nObservability & Monitoring\nDesign comprehensive monitoring, logging, and alerting (Prometheus, Grafana, Datadog, or similar)\nBuild dashboards for system health, performance, and business metrics\nImplement distributed tracing for microservices\nConduct capacity planning and performance analysis\nDrive reliability improvements through data-driven insights\nSecurity & Compliance\nImplement security best practices: identity management, secrets management, network policies\nWork towards or maintain security certifications (SOC 2, ISO 27001, or similar)\nConduct security audits and vulnerability remediation\nImplement data governance policies for AI pipelines and user data\nEnsure compliance with data privacy regulations (GDPR, CCPA)\nAutomation & Tooling Development\nWrite automation scripts and tools in Python for operational tasks\nBuild internal tooling for deployments, monitoring, and incident response\nDevelop runbooks, automation, and self-healing systems\nCreate APIs for infrastructure operations when needed\nMaintain high code quality and testing standards for tooling\nReliability & Incident Management\nParticipate in on-call rotation and lead incident response\nConduct blameless postmortems and drive action items\nBuild and maintain incident response playbooks\nImprove system resilience and failure modes\nCollaboration\nPartner with engineering teams on deployment strategies and architecture\nWork with security team on compliance and governance\nMentor engineers on operational best practices\nDocument systems, procedures, and runbooks\nKey requirements\n7+ years of experience in Platform Engineering, Site Reliability Engineering, DevOps, or Infrastructure Engineering roles\nDeployment expert: Deep experience with CI/CD pipelines, release strategies, and production deployments at scale\nMulti-cloud expertise: Hands-on experience with Azure and AWS required (GCP is a plus)\nOn-premise deployment experience: Linux system administration, bare-metal provisioning, networking\nTerraform expert: Deep experience writing and maintaining infrastructure as code\nObservability systems: Proven track record building monitoring, alerting, and metrics platforms\nSecurity mindset: Experience implementing security controls and best practices. Security certification preferred (CISSP, CEH, AWS/Azure Security Specialty, or similar)\nData governance: Understanding of data privacy, residency requirements, and governance frameworks\n Backend/scripting skills: Python (preferred) or Go for automation, tooling, and operational scripts\nKubernetes and container orchestration in production\nStrong Linux/Unix administration and scripting (Bash, Python)\nCI/CD platforms: GitHub Actions, GitLab CI, Jenkins, or similar\nVersion control and GitOps practices\nStrong problem-solving and debugging skills\nFluent in English (Spanish is a plus)\nNice-to-Have\nPython proficiency for automation and internal tooling\nExperience with cloud AI platforms (Vertex AI, Azure ML, AWS SageMaker)\nService mesh experience (Istio, Linkerd) or API gateways\nExperience with GPU workloads and ML infrastructure\nFinOps and cloud cost optimization\nCompliance frameworks experience (SOC 2, ISO 27001, HIPAA, FedRAMP)\nDatabase operations: PostgreSQL, Redis administration\nExperience with FastAPI or similar frameworks for internal tools\nContributions to open-source infrastructure projects\nBackground in hardware or semiconductor industries\nWork model & location expectations:\nTeam work model: Remote\n\nPrimary location: Open to Singapore or Japan \n\nWhy join us? \nAt Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30X30 mission. \nThis is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions. Consequently, see those ideas commercialized into products that will shape the future of hardware and computing, while collaborating with a global team of engineers and AI specialists. \nWe believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, with focus on formal consistency. If you're ready to take your expertise in artificial intelligence and physics to the next level, we want to hear from you!\nWorried about not meeting every qualification? Studies show that women and people of color are less likely to apply for jobs unless they meet every listed requirement. At Axiomatic-AI, we are dedicated to creating a diverse, inclusive, and authentic workplace. If this role excites you but your background doesn’t perfectly match every qualification, we still encourage you to apply. 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