Senior Infrastructure Engineer

About the role

ABOUT MACROSCOPE

Macroscope is building the infrastructure for the next generation of software development, where engineers direct fleets of agents, every change is automatically reviewed and verified, and organizations have a clear understanding of how their products and codebases are evolving.

Our mission is to give engineers more leverage and leaders more clarity, so teams can build better software, faster.

Macroscope is founded by former entrepreneurs who have started and sold multiple companies, and operated as product/engineering executives at public tech companies. We're fortunate to be supported by the best VC firms and angels in the business, including Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.

ABOUT THE ROLE

We’re looking for a Senior Backend Infrastructure Engineer to help shape and scale the foundation of Macroscope’s core services and inference platforms. You’ll play a key role in designing and implementing the distributed systems, infrastructure, and APIs that power our core product, while building the infrastructure needed to deploy and manage LLMs at scale.

You’ll lead projects focused on backend scalability, reliability, and performance, ensuring our systems can evolve alongside customer demand. You’ll partner closely with the engineering team to establish best practices across cloud infrastructure, CI/CD pipelines, observability, and production operations.

You’ll also work closely with our ML Research team to architect and build the infrastructure needed to support our growing ML research, training, and inference workloads.

As part of our small team, you’ll work directly with the founders, engineers, and designer to make architectural decisions that will help define the trajectory of our product and company.

Our technology stack: TypeScript/React (frontend), Go (backend), Temporal, Google Cloud (GCP), Postgres, Terraform, and custom-built AST "code walkers" in various languages (Go, TypeScript, Swift, Python, Rust).

QUALIFICATIONS

- Deep experience architecting and operating distributed backend systems at scale.

- Expertise in building resilient, performant, and maintainable backend services and APIs.

- Strong proficiency with cloud environments, ideally Google Cloud Platform (GCP), including networking, IAM, monitoring, and infrastructure as code (Terraform or equivalent).

- Experience building or operating infrastructure for modern LLM workloads, including inference serving, fine-tuning, and training workflows. Familiarity with techniques such as LoRA and reinforcement learning (RL) is a plus.

- Experience leading backend or infrastructure projects and driving architectural decisions in high-growth engineering environments.

- Hands-on experience with databases (SQL/Postgres), caching layers, and messaging systems.

- Familiarity with observability tools and practices, including logging, metrics, tracing, and alerting.