Founding Engineer, Platform

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 510 years
Compensation: $225000$300000 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

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.

Youll join a small engineering team with significant ownership and direct influence over the products 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.

• 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.

• 5 years of professional backend or platform engineering experience ideally within the 510-year range.

• A bachelors 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 companys hybrid arrangement.

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

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.

• 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.

• 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.

• Base salary: $225000$300000 listed range. The intake discussion indicates a target near $250000 cash and a hard cap of $250000 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-stage equity participation; candidates should evaluate the grant alongside the companys stage and offer terms.

• Own the platforms core: Build the infrastructure that powers every customer workflow.

• Solve difficult backend problems: Work on data consistency throughput queues database performance and high availability.

• Shape an AI-native architecture: Contribute to agent-first workflows a custom compiler and an internal evaluation stack.

• Operate with founding-level autonomy: Own projects from initial scoping through production outcomes.

• Influence product direction: Work in a small team without traditional product-management layers.

• Build with a modern stack: Work with TypeScript Effect PostgreSQL Redis and modern frontend and data tools.

• Make a visible impact: Improve the reliability and performance of infrastructure customers depend on every day.

• Participate in early-stage upside: Receive meaningful equity alongside a competitive engineering compensation package.