Senior Platform Engineer

About us:
Axiomatic 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.
Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.
We 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.
Position Overview
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.
You will:
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.
Your mission
Deployment & CI/CD
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
Infrastructure & Cloud Operations
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
Infrastructure as Code
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
Observability & Monitoring
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
Security & Compliance
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)
Automation & Tooling Development
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
Reliability & Incident Management
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
Collaboration
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
Key requirements
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)
Nice-to-Have
Python proficiency for automation and internal tooling
Experience with cloud AI platforms (Vertex AI, Azure ML, AWS SageMaker)
Service mesh experience (Istio, Linkerd) or API gateways
Experience with GPU workloads and ML infrastructure
FinOps and cloud cost optimization
Compliance frameworks experience (SOC 2, ISO 27001, HIPAA, FedRAMP)
Database operations: PostgreSQL, Redis administration
Experience with FastAPI or similar frameworks for internal tools
Contributions to open-source infrastructure projects
Background in hardware or semiconductor industries
Work model & location expectations:
Team work model:
Hybrid. Open to Remote
Primary location:
Barcelona / Boston
On-site expectations:
This role can be hybrid or remote. For hybrid arrangements, we would expect ~2 days per week in the office (with flexibility). Occasional travel to our Barcelona or Boston office may be required if remote.
Hiring Manager note:
Given that a significant portion of the team works remotely, we are open to flexible working arrangements, including hybrid or fully remote options depending on location and team needs.
Why join us?
At Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30X30 mission.
This 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.
We 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!
Worried 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. You could be the perfect fit for this position or another opportunity with us.