Member of Technical Staff, Software Engineering

Why this work matters

Touchdown starts with people doing real work: teach the team, build one useful AI system, manage what runs, and measure what still breaks. We follow repeated limits through software, inference, kernels, memory, hardware, materials, and manufacturing research only when the evidence earns the next layer. The ambition is broad. The work is always bounded by a user, a test, and a receipt.

Overview

This is a general software engineering role, not a front-end-only role. You will build the product and operational software around customer workflows: interfaces, APIs, data systems, evaluation paths, internal control planes, and the web surfaces needed to operate them. The work sits between a user request and the underlying models and infrastructure, so reliability, data lineage, permissions, and clear failure states matter as much as visual polish.

What you will own

• Build and maintain customer-facing workflows, APIs, backend services, data models, and internal operating tools.
• Turn manual delivery and research paths into reliable software without hiding the judgment that still requires a person.
• Connect identity, customer inputs, model execution, evaluation, artifacts, usage records, and support workflows.
• Design explicit state transitions for queued work, retries, failures, human review, promotion, and rollback.
• Protect customer and research data through scoped access, validation, retention controls, and auditable boundaries.
• Own deployment, monitoring, incident follow-up, documentation, and the developer experience around what you ship.

Technical territory

TypeScript and Python applications; APIs and background jobs; relational and object data; authentication and authorization; file and artifact handling; evaluation workflows; model and provider adapters; observability; billing evidence; secure web interfaces; deployment and operations. The exact stack can change, but the contracts and failure behavior cannot be vague.

Representative outputs

• Versioned APIs, schemas, state machines, permissions, and retention rules for one complete customer or internal workflow.
• Tested interfaces connecting identity, inputs, model execution, evaluation, artifacts, usage, and human review.
• Operational dashboards, alerts, recovery procedures, and post-incident changes tied to named failure modes.
• Deployment and developer documentation that lets another engineer reproduce, operate, and extend the system.

What success looks like

• A user can complete the intended workflow without an engineer manually repairing the path.
• Inputs, outputs, decisions, and artifacts can be traced without exposing sensitive content.
• Retries, partial failures, permissions, and rollback are designed rather than improvised.
• The software remains understandable and testable as models and infrastructure change.

What you bring

• Production software experience across backend, full-stack, platform, or data systems.
• Strong testing, debugging, API design, data-modeling, and asynchronous-work fundamentals.
• Experience designing for authentication, authorization, validation, and operational failure.
• Ability to make pragmatic tradeoffs without hiding failure states or creating unowned manual work.
• Clear ownership from issue discovery through deployment, monitoring, and verification.
• Ability to explain implementation choices to both technical and non-technical teammates.

Helpful experience

• TypeScript and Python
• Cloud and self-hosted systems
• Security and privacy engineering
• AI applications or evaluation systems
• Data pipelines and developer tooling

How the role works

• Full-time role.
• San Francisco / Bay Area preferred. Remote within the United States may be considered for the right person.
• Scope, start date, and employment details are discussed during the process.