AI Platform Architect

About Aalo Atomics

Aalo Atomics is pioneering a new era in clean energy with factory‑fabricated microreactors designed to deliver affordable, scalable, and reliable nuclear power. Our mission is to make nuclear energy globally accessible, starting with the Aalo-1, a 10 MWe reactor leveraging cutting‑edge safety, modularity, and efficiency. Based in Austin, TX, we’re rapidly growing as we work to deploy the world’s first fleet of advanced microreactors.

Join us and help revolutionize energy for a sustainable future.

We’re hiring an AI Platform Engineer to maintain, evolve, and continuously improve the horizontal systems that make AI usable, secure, and scalable across the company.

At Aalo, AI is becoming part of the operating system of the company. This role focuses on the horizontal foundation: shared gateways, orchestration, observability, security boundaries, deployment patterns, and platform architecture that let many AI solutions be built safely on top.

This role sits at the center of every AI system we deploy.

You will work as part of a small, highly collaborative AI team maintaining and evolving an existing internal platform that powers AI across the company.

Your job is to maintain, harden, and evolve the shared substrate that other engineers and agents build on top of.

This is a software and platform engineering role with strong architecture, security, controls, integration, infrastructure, and operational governance responsibilities.

Examples of the platform systems and capabilities this role may touch include:

• AI model gateways, routing, token management, model lifecycle administration, and cost controls
• Agent harnesses, shared skills, tool orchestration, and execution runtimes
• Observability, evaluation, feedback, and audit trails for AI-generated outputs
• Identity, access control, data boundaries, and secure enterprise authentication
• Shared integration layers across manufacturing, engineering, finance, HR, logistics, and document systems
• Deployment infrastructure, CI/CD, and infrastructure as code for AI services
• Internal APIs, reusable services, admin tooling, and operational control planes for AI systems
• Workflow orchestration, browser automation, and background job execution systems
• Platform patterns for regulated, high-reliability, and mission-critical AI applications

Common technology categories and platform patterns in the stack include:

• Backend application development
• Internal web applications and admin interfaces
• Relational and document-oriented databases
• APIs and service-oriented backend systems
• Frontend and internal admin web application frameworks
• Containers, CI/CD, and infrastructure as code
• Cloud platforms, secure storage, identity, and secrets management
• Model providers, gateways, access control, and policy enforcement
• AI coding agents, agent harnesses, orchestration frameworks, and shared tooling
• Observability, evaluation, telemetry, security controls, and feedback systems

• Maintain, evolve, and continuously improve platform architecture, service boundaries, and reusable primitives for AI systems
• Build and harden gateways, orchestration layers, shared tools, and integration frameworks
• Implement deployment patterns, CI/CD workflows, and infrastructure best practices that keep AI systems reliable at scale
• Review, debug, and refine AI-generated code in mission-critical and shared systems
• Build observability, evaluation, feedback, and usage telemetry systems that let AI solutions be measured, audited, and continuously improved
• Establish security boundaries, data access patterns, controls, policy guardrails, and auditability for internal AI systems
• Work closely with solutions engineers and other stakeholders to enable reusable platform capabilities that compound in value over time

Strong engineering fundamentals

• You can design platform systems with clear APIs, service boundaries, data models, and integration patterns
• You write clear, maintainable code and have strong judgment around reliability, security, and operational quality
• You know when to move carefully on shared or mission-critical systems and when to avoid unnecessary complexity

High output and follow-through

• Y…