Software Engineer

Recruiting From Scratch•Mountain View, CA

1d•Hybrid

About The Position

The company operates in fast 4–6 week R&D cycles, focusing on building scalable systems that combine data infrastructure, machine learning, and agent-based automation. The team is small, consisting of 12 highly technical engineers with experience from top-tier tech companies and high-growth startups. The company has successfully raised $25M from leading investors and is experiencing strong early traction with both enterprise and SMB customers. This role offers a rare opportunity to join a fast-growing AI company that is building autonomous systems for performance marketing at scale. The successful candidate will work on foundational backend and data infrastructure, powering AI agents used by real customers, and will have a direct impact on product outcomes and system design. The team operates at high velocity with significant technical depth, and engineers are expected to take ownership of large parts of the stack from day one.

Requirements

3–8 years of experience in backend or data engineering roles
Strong proficiency in Python (Django experience preferred)
Experience building production systems at scale
Strong CS fundamentals and system design ability
Experience with data infrastructure, distributed systems, or ML pipelines
Exposure to cloud environments (AWS, GCP, or similar)
Experience in startup or high-growth engineering environments
Ability to operate in fast-paced, ambiguous environments

Nice To Haves

Experience in ads, search, recommendation systems, or data-heavy platforms
Experience with ML infrastructure or MLOps systems
Experience working at high-growth startups or top-tier tech companies
Familiarity with Kubernetes or distributed compute systems
Strong academic background (top CS programs preferred)
Exposure to AI/agent-based systems

Responsibilities

Build robust backend systems and APIs using Python and Django
Design scalable data infrastructure powering AI agents and marketing automation systems
Work on distributed systems supporting high-throughput data pipelines
Collaborate with ML engineers to integrate models into production systems
Build systems for reliability, scalability, observability, and performance
Work across backend, data, and ML infrastructure layers
Contribute to system design and architectural decisions
Participate in rapid 4–6 week product iteration cycles
Ensure high engineering standards through code reviews and best practices
Partner cross-functionally to translate business needs into technical systems