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Macroscope is building infrastructure for the next generation of software development, where engineers direct fleets of AI agents, every change is automatically reviewed and verified, and organizations have clear visibility into how their products and codebases are evolving.
We're seeking 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 the core product, while building the infrastructure needed to deploy and manage LLMs at scale.
Key responsibilities:
- Lead projects focused on backend scalability, reliability, and performance, ensuring systems evolve alongside customer demand
- Partner closely with the engineering team to establish best practices across cloud infrastructure, CI/CD pipelines, observability, and production operations
- Work with the ML Research team to architect and build infrastructure supporting growing ML research, training, and inference workloads
- Work directly with founders, engineers, and designers to make architectural decisions that define the product and company trajectory
- Design and implement resilient, performant, and maintainable backend services and APIs
Tech stack: TypeScript/React (frontend), Go (backend), Temporal, Google Cloud Platform (GCP), Postgres, Terraform, and custom-built AST code walkers in various languages (Go, TypeScript, Swift, Python, Rust).
The company was founded by former entrepreneurs who have started and sold multiple companies and operated as product/engineering executives at public tech companies. Backed by Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.
Culture: Extremely high-agency, flat organizational structure, self-motivated individuals driving contributions to the mission. This is an early-stage startup requiring exceptional talent willing to work extremely hard on something high-risk. You act like an owner, put immense care into what you build, and care deeply about the mission.
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 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
- Use AI tools to accelerate your work as an engineer and stay current with emerging technologies and best practices
- Strong experience with Go, the primary backend language, is highly preferred
- Bonus: experience with Temporal or similar durable execution/workflow orchestration systems
