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

* Primary location:

Boston, US

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.