Albert's mission is to help chemists change the world. We're building the first AI-native operating system for materials science, and we need the engineering foundation to match. If you care deeply about API platform design, performance, and building things that last at scale, this role is for you.

About the role

We're looking for a Senior Staff Engineer to own the API platform and backend infrastructure that underpins Albert OS as it evolves toward a full PaaS offering. This isn't a greenfield role — we're mid-transition, and the job is to lead the architecture, set the patterns, and bring the platform across without compromising reliability.

You'll own how the platform performs and scales across a multi-tenant environment operating at sub-second latency SLOs. You'll be a trusted technical partner to platform engineering, product engineering, and security teams. We're also moving toward AI-native, spec-driven development — and we want this person to lead from the front on that shift.

What you'll do

Cloud architecture and platform strategy

• Own the roadmap for our Node.js API platform, ensuring it scales, stays secure, and stays easy for teams to build on.
• Design and maintain access control systems, authorization patterns, and ACL frameworks that work consistently across services.
• Define and enforce service-to-service interaction patterns, including authentication, trust boundaries, and inter-service contracts.
• Build and maintain shared backend libraries, frameworks, and abstractions that improve consistency and velocity across product engineering teams.
• Design and evolve event-driven architecture patterns — including async messaging, event sourcing, and queue-based workflows — across the platform.
• Partner with product and engineering to establish platform primitives that teams can build on reliably.

Performance and reliability

• Own performance and reliability for a multi-tenant platform operating at sub-second latency SLOs.
• Identify and resolve bottlenecks across the request path — from API gateway through to data layer.
• Define reliability standards, runbooks, and incident response patterns for platform-level failures.
• Instrument the platform for observability: traces, metrics, and alerts that surface problems before partners do.

Developer experience and DevOps

• Build and maintain tooling, automation, and CI/CD pipelines that improve reliability and shipping velocity.
• Establish best practices for infrastructure as code, containerization, observability, and cost optimization.
• Embed security, compliance, and reliability standards into the development lifecycle by default.

Technical leadership

• Lead the architecture through a platform transition — setting direction, establishing patterns, and holding the bar on reliability throughout.
• Serve as a senior technical authority across the API platform, backend architecture, and cloud infrastructure.
• Own and evolve engineering guidelines across the org — coding standards, architectural patterns, review processes, and AI tooling norms.
• Champion AI-native and spec-driven development practices, setting the standard for how engineers work with AI tooling day-to-day.
• Align long-term technical direction with business objectives in partnership with Product, TPM, and Security leadership.

People leadership:

• Manage and mentor a small team of 3–4 platform engineers, providing technical guidance, career development, and day-to-day support.
• Set clear expectations, run structured reviews, and build a team culture of ownership and craft.
• Partner with engineering leadership on hiring, onboarding, and growing platform engineering talent.

What you bring

Required:

• 12+ years in backend platform or cloud engineering roles.
• Deep expertise in NestJS and Node.js-based backend architectures at scale.
• Deep AWS expertise and strong understanding of distributed systems: microservices, containers, event-driven architectures.
• Strong experience designing access control systems, authorization frameworks, and IAM
• Hands-on experience building shared libraries and platform abstractions consumed by multiple product teams.
• Demonstrated track record of owning performance and reliability in multi-tenant SaaS environments with strict latency SLOs.
• Expertise with IaC (Terraform, CDK, or CloudFormation) and CI/CD pipelines.
• Strong networking, security, observability, and performance engineering fundamentals.
• Clear communication and the ability to influence across technical and non-technical stakeholders.

Preferred:

• Exposure to Azure, GCP, or other cloud environments.
• Experience in SaaS or PaaS at enterprise scale.
• Background in product engineering with a track record of shaping technical direction.
• Strong familiarity with AI-native development workflows and spec-driven development practices.
• Knowledge of AI agents, LLM integration patterns, and how they apply to platform and backend engineering.

Why this role

You'll own the platform layer that every product team builds on — API design, authorization, service interactions, and shared infrastructure — and lead it through a critical transition without dropping the reliability bar. It's a role with real authority, real scope, and direct impact on what Albert can deliver to the scientists who use it every day.

Key Competencies

• Builder Mindset: Wants to create foundational systems that others build on.
• Curiosity: Genuine interest in how your work enables scientific discovery.
• Rigor: Commitment to quality — AI makes mistakes confidently, and our customers won't accept hand-waving.
• Collaboration: Partners effectively with engineers across Produce Engineering, AI/ML, Enterprise Engineering.
• Adaptability: Comfortable in a dynamic, fast-moving environment where priorities shift.

Why Albert

• Revenue from day one. The product is loved and used by thousands of users.
• Small team. Flexible hours. Collaboration over process.
• No micro-management. You'll own your work.
• Building software for a sustainable future.

Albert helps chemists change the world by building technology that understands how they work. As chemists ourselves, we know what it’s like when software doesn’t work the way you do — stuck with systems built by people who never spent a day at the bench. That’s why we created Albert OS, the first AI-native operating system for materials science, designed to remove every obstacle between curiosity and discovery.