Software Engineer

dynamism; San Francisco (CA); On-site; USD 400,000 - 500,000; Full time

Job summary

Dynamism is hiring a Software Engineer to own end-to-end, full-stack training environments for applied AI systems. You will implement scalable environments with realistic state, data models, tool contracts, and verifiers to turn rollouts into meaningful training signals.

The role emphasizes speed with rigor, and building across domains with high correctness. Candidate should thrive in a fast-paced setting, transform feedback into code, data, and tasks, and ship in ambiguity while upholding

Qualifications

• Strong full-stack experience with TypeScript and modern web tech.
• Ability to design complex, deterministic training environments.
• Experience with containerization, cloud services, and test tooling.

Responsibilities

• Own high-fidelity training environments from design through rollout.
• Build full-stack environments with realistic, resettable state across many rollouts.
• Define agent-facing tool surfaces, data models, and programmatic verifiers.
• Ensure robust, deterministic behavior and fast feedback loops with domain experts.

Skills

TypeScript

Web fundamentals

Full-stack development

Testing

Docker

AWS

Tools

Postgres

SQLite

Node.js

Claude Code

Vitest

Playwright

Job description

Software Engineer Full time · San Francisco or New York · On site

Compensation: $400K to $500K base salary plus meaningful equity
Location: San Francisco or New York, on site

At Dynamism, we partner with breakout startups backed by Sequoia, a16z, and Y Combinator to help them hire engineers with founder energy, people who build fast, think like owners, and thrive in zero to one environments.

We're hiring for this role at an early stage applied AI company building high fidelity environments, tasks, data, and evaluation infrastructure that help frontier models learn reliable behaviour in real work. The company works closely with frontier AI labs and enterprises, and is backed by Sequoia Capital, Menlo Ventures, BCV, and SV Angel. Its engineering first team brings together former founders, researchers, and deeply technical builders who value speed with rigor, truth over comfort, and precision under pressure.

The Role

You will own high fidelity training environments from design through the first graded agent rollout. Each environment is a full-stack reconstruction of how real work happens, including the product surface, data model, business logic, tool contracts, tasks, and programmatic verifiers that turn rollouts into useful training signal.

What You'll Own

• Full-stack environments with realistic, resettable state across large numbers of rollouts
• Agent-legible tool surfaces, task definitions, seed data, and programmatic verifiers
• Complex multi-step workflows with coherent state, simulated stakeholders, and real-world failure modes
• Programmatic review systems that maintain correctness and robustness as the environment library grows
• Fast feedback loops with domain experts and multiple coding agents working in parallel
• Are a deeply technical full-stack builder with strong TypeScript and web fundamentals
• Have product taste and can determine which details make a reconstruction faithful
• Can turn direct feedback from domain experts into code, data, tasks, and quality checks
• Think in determinism, invariants, contracts, and failure modes, not only features
• Ship quickly in ambiguity while maintaining a high bar for correctness
• TypeScript, Svelte or React, Node.js, Postgres or SQLite, Python, Docker, AWS, MCP, Vitest, Playwright, Claude Code
• Built a full-stack product from zero to one
• Created realistic simulations, test harnesses, or complex workflow software
• Worked on AI evaluations, agent tooling, or low-level infrastructure
• Used multiple coding agents to increase delivery speed without losing quality
• Compensation: $400K to $500K base salary plus meaningful equity
• Location: San Francisco or New York, on site
• Full time and on site

This role will not suit someone looking for routine, a narrow technical silo, or a management only position. The team moves quickly, expects direct ownership, and does not trade quality for speed.