Founding Engineer, Platform

Founding Engineer, Platform

Location

San Francisco Bay Area, California

Work Arrangement: Hybrid — in-person attendance required Position: Full-time Company Stage: Early-stage startup Experience: 5+ years of backend or platform engineering experience; ideally 5–10 years Compensation: $225,000–$300,000 listed base salary Equity: Approximately 0.5%–1.0% Relocation: No relocation support available Visa: Visa transfers, including eligible OPT and H-1B transfers, are listed as supported

Company Description

We are building an AI-native platform that helps go-to-market teams design, deploy, and run complex workflows. The platform connects to customer systems through APIs, a user interface, and a browser extension, with AI agents playing a central role in how workflows are created and executed.

As the platform scales, the team is investing in the infrastructure that powers every customer workflow, including scheduling, queues, integrations, data processing, and reliability. The engineering roadmap includes a custom workflow compiler and an in-house evaluation stack designed to make agent-driven workflows more reliable and effective.

You'll join a small engineering team with significant ownership and direct influence over the product's technical direction. This is an opportunity to work on core platform infrastructure, solve high-throughput backend challenges, and shape the architecture of an AI-native product from an early stage.

What You Will Do

• Own the workflow engine: Build and evolve the backend systems that schedule, execute, and manage customer workflows.

• Scale shared infrastructure: Design systems that handle high-volume data processing, concurrent workloads, and increasing customer demand.

• Improve database performance: Solve challenges involving database efficiency, data consistency, shared-table workloads, and reliable processing at scale.

• Build production-grade job systems: Develop or improve queues, schedulers, data pipelines, and other infrastructure that supports customer-facing workflows.

• Shape platform architecture: Make technical decisions that account for reliability, scalability, maintainability, and the impact on the wider system.

• Advance agent-first infrastructure: Design systems and interfaces that help AI agents understand workflow state, interpret errors, and take appropriate corrective action.

• Contribute to the workflow compiler: Help evolve the workflow engine toward a custom compiler and more sophisticated execution infrastructure.

• Improve AI reliability: Contribute to the internal evaluation stack and mechanisms for testing, validating, and improving agent outputs.

• Own features end-to-end: Take projects from ambiguous requirements and technical scoping through implementation, deployment, and customer outcomes.

• Drive product direction: Work closely with the technical co-founder and engineering leadership to identify priorities and make product and platform decisions.

• Close the loop on outcomes: Monitor how shipped features perform, identify issues, and take responsibility for improvements rather than stopping at implementation.

Ideal Candidate Background

Required Experience

• 5+ years of professional backend or platform engineering experience, ideally within the 5–10-year range.

• A bachelor's degree is required.

• Experience building and operating production backend systems that handle high-volume workloads.

• Demonstrated experience with job systems, queues, schedulers, or data pipelines at scale.

• Experience with scalability, database performance, data consistency, and high availability.

• Experience working with shared infrastructure or systems that other teams, services, or products depend on.

• Strong TypeScript experience, ideally including Effect or functional programming patterns.

• Experience at an early-stage startup, preferably seed through Series A or Series B, or as a founding engineer or startup founder.

• Demonstrated ability to take a project from an ambiguous idea through production with limited direction.

• Strong technical judgment and the ability to anticipate how architectural decisions affect the broader platform.

• Willingness to work in the San Francisco Bay Area under the company's hybrid arrangement.

• No relocation support is available, so candidates outside the area must be able to manage their own relocation.

Technical Skills

Core Engineering

• Backend and platform engineering.

• Production job systems, queues, schedulers, and data pipelines.

• High-throughput data processing and shared infrastructure.

• Database performance, data consistency, and reliability.

• Distributed systems and production operations.

• API design and service integrations.

• System design, technical trade-offs, and end-to-end ownership.

Relevant Technologies

• Primary language: TypeScript.

• Functional programming: Effect or comparable functional TypeScript experience.

• Database: PostgreSQL.

• Infrastructure and data: Redis, queues, workflow engines, and high-volume data processing.

• Frontend and platform tooling: React, Vite, TanStack, ElectricSQL.

• AI infrastructure: Agent-oriented workflows, evaluation systems, and reliable agent interactions.

• Compiler systems: Workflow execution engines and custom compiler development.

Candidates do not need experience with every technology listed. Prioritize production infrastructure depth, strong backend engineering fundamentals, and the ability to reason about reliability and scale. Experience with Effect is a stated baseline requirement, so assess practical familiarity carefully.

Preferred Background

• Experience as a founding engineer, early engineer, or technical co-founder.

• Experience at a seed-stage through Series B startup.

• Experience building infrastructure used by multiple teams, services, or customer workflows.

• Experience operating high-throughput job systems, queues, or data pipelines.

• Experience processing large volumes of unstructured data.

• Experience with functional TypeScript and Effect.

• Experience with Postgres performance tuning and Redis.

• Experience building workflow engines, orchestration platforms, or execution systems.

• Experience building AI-native products, agent infrastructure, or evaluation frameworks.

• Experience designing systems where reliability and uptime are directly visible to customers.

• Experience owning product direction in an organization without dedicated product managers.

Working Style and Culture

• High ownership: Takes responsibility for projects from scoping through shipping and ongoing improvement.

• Staff-level individual contributor: Combines deep technical execution with strong architectural judgment.

• Autonomous: Can make progress on ambiguous projects without needing detailed instructions.

• Product-minded: Connects infrastructure decisions to customer workflows and product outcomes.

• Systems thinker: Understands how changes in one component affect reliability and performance across the platform.

• Startup-oriented: Comfortable with limited process, shifting priorities, and broad responsibilities.

• Reliability-focused: Treats uptime, data consistency, and production errors as core engineering concerns.

• Outcome-driven: Measures success by what works in production and how it improves the product.

• Communicative: Can clearly explain technical decisions, trade-offs, failures, and lessons learned.

Compensation and Benefits

• Base salary: $225,000–$300,000 listed range. The intake discussion indicates a target near $250,000 cash and a hard cap of $250,000, which conflicts with the published range. Confirm the approved cash ceiling before discussing offers.

• Equity: Approximately 0.5%–1.0%, with the grant expected to vary by candidate and offer structure.

• Work arrangement: Hybrid in the San Francisco Bay Area; confirm the precise in-office schedule.

• Relocation: No relocation support available.

• Visa support: Eligible visa transfers, including OPT and H-1B transfers, are listed as supported; confirm individual eligibility.

• Founding-level ownership: Opportunity to shape core infrastructure and make consequential architectural decisions.

• Technical scope: Work on workflow engines, high-throughput backend systems, functional TypeScript, and agent-first infrastructure.

• Direct collaboration: Work closely with the technical co-founder and engineering leadership.

• Equity upside: Meaningful early-st