Software Engineer (Mid-level to Staff+)

Recruiting From Scratch•San Francisco, CA

6d•Onsite

About The Position

We are building an AI platform that enables companies to run their businesses through intelligent software agents. Customers can describe an outcome in plain English, and the platform takes ownership of the work across the tools and systems their businesses already use. The company has raised more than $42M from leading investors and is experiencing exceptional growth, with year-to-date growth exceeding 1000%. The product has reached a major inflection point and is becoming an industry-defining platform for AI-driven work. The engineering team is building across product, backend platform, and AI infrastructure. Engineers have broad ownership and are expected to follow important problems wherever they lead—from interaction design and client architecture to APIs, data models, agent runtimes, storage, distributed systems, and production infrastructure. This is a hands-on environment for unusually strong engineers who care about first-principles reasoning, strong computer-science fundamentals, and shipping high-quality production software.

Requirements

2–15 years of experience shipping production software, with strong depth in TypeScript and full-stack/backend engineering.
Experience at highly selective companies, including top Big Tech companies or well-known startups.
Clear evidence of technical growth and progression.
Strong computer-science fundamentals and ability to reason from first principles.
Demonstrated experience owning meaningful production systems after launch.
Comfortable working as a hands-on IC and writing code every day.
Strong production experience with TypeScript.
Experience building across a Node.js backend and React frontend.
Hands-on experience with APIs and modern web application architecture.
Experience with GCP and Docker.
Ability to own deployments and debug at the container/Linux level.
Strong understanding of software engineering fundamentals, system design, and production reliability.
Ability to understand and debug systems across application, data, infrastructure, and runtime layers.
Comfortable working across role boundaries rather than operating within a narrow specialization.
Experience building polished user-facing products.
Strong product instincts and ability to translate ambiguous problems into simple, intuitive experiences.
Experience owning features end to end.
Ability to prototype quickly and iterate based on customer feedback.
Strong attention to usability, performance, correctness, and reliability.
Experience building backend APIs and production services.
Experience with identity, permissions, workspaces, billing, payments, analytics, or similar core systems is valuable.
Experience with connectors, authentication, webhooks, automations, and third-party integrations is preferred.
Strong understanding of data modeling, abstractions, reliability, security, and operational simplicity.
Strong interest in AI systems and current model capabilities.
Hands-on experience using modern AI tools and models.
Ability to reason about agent systems, orchestration, tool execution, context, memory, evaluation, and reliability.
Experience with databases, Kubernetes, networking, queues, cloud infrastructure, or distributed systems is valuable.
Professional AI experience is not required if the candidate demonstrates serious hands-on engagement with AI and strong technical depth.
Production experience with core infrastructure such as databases, distributed systems, compilers, operating systems, runtimes, or execution environments is highly valued.
Strong debugging skills across application and infrastructure layers.
Experience owning deployments and production operations.
Ability to reason about performance, reliability, security, safety, cost, and operational simplicity.
Exceptional problem solver with strong computer-science fundamentals.
Thinks from first principles and builds clear mental models.
High ownership and personal accountability.
Comfortable with ambiguity and rapidly changing priorities.
Prefers responsibility over process.
Learns quickly and adapts to new technologies.
Strong written and verbal communication.
Can discuss technical work clearly and succinctly.
Cares deeply about quality and real-world outcomes.
Curious about AI and actively follows the field.
Uses AI deeply in their own work and forms independent views about the technology.
Eager to remain a hands-on IC and write code every day.

Responsibilities

Build the user-facing product across web, mobile, onboarding, and other product surfaces.
Design clear and intuitive interactions for delegating work to AI agents, monitoring progress, handling uncertainty, and using agent output.
Build backend APIs and services that power the product and support accounts, workspaces, permissions, billing, payments, and analytics.
Develop reliable infrastructure for connectors, authentication, webhooks, automations, and third-party integrations.
Design simple abstractions and data models that can support a rapidly evolving product.
Build the core infrastructure behind AI agents, including orchestration, tool execution, state management, evaluation, and failure recovery.
Develop context-management, filesystem, memory, storage, and sandboxed execution systems.
Work on model routing and serving, databases, Kubernetes, networking, queues, and cloud infrastructure.
Make long-running agent workloads faster, safer, more reliable, and more cost-efficient.
Own features and systems end to end, from early product thinking and prototyping through production deployment and ongoing improvement.
Debug problems wherever they lead, from application code through infrastructure and container/Linux environments.
Prototype quickly, learn from customers, and turn successful ideas into durable production systems.
Work across the stack and across role boundaries whenever that is the best way to solve the problem.
Personally build and ship software every day as a hands-on individual contributor.