Founding Backend Engineer - Distributed Systems / AI Infrastructure (San Francisco)

Location: San Francisco, CA (In-Person)

Compensation: $150K-$300K Base + Equity + Benefits

Stack: Python, distributed systems, cloud infrastructure, Kubernetes, Docker, infrastructure-as-code, observability, production ML systems, and high-throughput backend services.

TLDR

• Our client is building AI-powered systems that transform complex unstructured information into structured, actionable intelligence, addressing a massive opportunity at the intersection of AI and enterprise software.
• This is a true founding engineer opportunity where one of the earliest technical hires will help define the architecture, engineering culture, and long-term technical direction of the company.
• Engineers own infrastructure and backend systems end-to-end, from initial prototypes through production deployment, reliability, scalability, and enterprise-grade operations.
• The role combines backend engineering, platform engineering, DevOps, and production AI infrastructure, making it ideal for candidates who enjoy broad technical ownership and solving complex systems problems.
• Candidates will work directly with founders and researchers while building the foundational systems that enable the company’s future growth and product success.

Requirements

• Experience building and operating production backend systems with strong ownership across architecture, deployment, reliability, and performance.
• Strong backend engineering skills with Python as a primary language; experience with additional systems languages such as Rust, Go, Java, or C++ is a plus.
• Experience designing and operating distributed systems, asynchronous processing workflows, message queues, caching systems, or other high-throughput backend architectures.
• Strong cloud infrastructure experience, including containerization, orchestration, deployment automation, and infrastructure management.
• Ability to operate independently in fast-moving startup environments while driving projects from concept through production.

Bonus Skills

• Experience serving machine learning, multimodal AI, GPU-intensive, or other compute-heavy production workloads.
• Experience with Kubernetes, Docker, Helm, Terraform, Pulumi, or similar infrastructure tooling.
• Experience supporting enterprise deployments, self-hosted environments, or hybrid cloud architectures.
• Familiarity with observability, incident response, reliability engineering, and production operations.
• Experience working closely with AI research teams to bring research systems into production environments.

Responsibilities

• Architect, build, and scale the core backend systems that power the company’s AI products and platform capabilities.
• Own production infrastructure end-to-end, including deployment workflows, monitoring, reliability, performance, and operational excellence.
• Design distributed systems capable of supporting high-throughput workloads and growing customer demand.
• Build tooling, automation, and platform capabilities that improve developer productivity and system reliability.
• Partner closely with founders and research teams to transform experimental AI systems into scalable production solutions.
• Establish engineering standards, infrastructure practices, and operational processes that support long-term company growth.

About

• Our client is building advanced AI systems that help organizations unlock value from complex unstructured information, combining cutting-edge machine learning with practical enterprise applications.
• Founding Backend Engineers play a critical role in the company’s success, owning the infrastructure and platform foundations that enable both product development and future scale.
• This is a highly autonomous role with significant ownership across backend architecture, infrastructure strategy, deployment systems, and engineering best practices.
• The role provides deep exposure to distributed systems, cloud infrastructure, production AI workloads, platform engineering, and the challenges of scaling frontier AI technologies into reliable products.