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Clera

Software Engineer - Full Stack

San Francisco$120k–$150kfulltimemidAdded 1 month ago

About this role

An AI-native adtech startup seeks a Full Stack Software Engineer to own end-to-end technical projects across advertiser platforms, attribution systems, and analytics pipelines. You'll build scalable backend services, optimize databases, and collaborate with GTM teams to translate business needs into production solutions in a fast-paced early-stage environment.

What you'll do

  • Own technical projects from design through deployment, testing, and production maintenance
  • Build and maintain backend systems and production APIs (REST, gRPC) with focus on scalability
  • Operate and troubleshoot production services including monitoring, observability, and incident response
  • Design and optimize PostgreSQL schemas for analytical and transactional workloads
  • Deploy and manage AWS cloud infrastructure in production environments
  • Develop analytics, attribution, and event-driven data pipelines for measurement and reporting

What they're looking for

  • Python (Django and/or FastAPI)
  • Backend systems and API design
  • AWS cloud services
  • PostgreSQL optimization and schema design
  • REST API design and async patterns
  • Production monitoring and observability
  • Data pipeline development
  • Docker and containerization (nice to have)

Benefits

  • Salary: $120,000–$150,000 USD annually
  • Early-stage equity opportunity
  • On-site role in San Francisco
  • High-impact work at intersection of engineering and go-to-market
  • Full project ownership across infrastructure and product
  • Collaborative environment with cross-functional stakeholders
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a backend project you owned end-to-end in production. How did you handle deployment, monitoring, and an incident if one occurred?
  • Tell us about your experience with Python (Django or FastAPI). How have you designed and optimized REST APIs for scalability?
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