Forward Deployed Software Engineer

dynamism; San Francisco (CA); On-site; USD 350,000 - 450,000; Full time

Benefits offered by this job

Built or led an early-stage company

Experience with AI evaluations

Frontier model collaboration

Deployment infrastructure

Job summary

Dynamism in San Francisco is seeking a Forward Deployed Software Engineer to build software that makes partner deployments fast, repeatable, and reliable. You will work across integrations, environment runtimes, data, task generation, and evaluation tooling in close collaboration with researchers and engineering teams.

This full-time, on-site role requires a technical generalist with ownership mindset and experience with Python and TypeScript, comfortable across systems and security constraints.

Qualifications

• Experience with Python and TypeScript in production environments.
• Familiarity with distributed systems and data tooling.
• Experience building AI-enabled evaluation/workflow tooling is a plus.

Responsibilities

• Build tooling and services for repeatable deployments
• Integrate with partner infrastructure under real security, reliability, and data constraints
• Develop environment runtimes, task pipelines, realistic data, and evaluation harnesses
• Debug across model behavior, software, data, and infrastructure failure modes
• Ensure systems scale in deployment volume and complexity

Skills

Python

TypeScript

Distributed systems

Data tooling

AI workflows

Tools

Containers

Job description

Forward Deployed Software Engineer

Full-time · San Francisco · On-site

Compensation: $350K to $450K base salary plus meaningful equity

Location: San Francisco, 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 environment. 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 behavior 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 build the software that makes each partner deployment fast, repeatable, and difficult to break. You will work across integrations, environment runtimes, data, task generation, and evaluation tooling while staying close to the researchers and technical teams using the work.

• Tooling and services that turn bespoke environment and evaluation work into repeatable deployments
• Integrations with partner infrastructure under real security, reliability, and data constraints
• Environment runtimes, task pipelines, realistic data, and evaluation harnesses
• Debugging across model behavior, software, data, and infrastructure failure modes
• Systems that preserve quality as deployment volume and complexity grow

What You'll Own

• Have founded a company, worked as an early engineer, or owned outcomes in a high agency environment
• Are a technical generalist who can cross engineering, research, data, and partner-facing work
• Can communicate with clarity while priorities and context change quickly
• Use AI agents deeply while retaining your own technical taste and judgment
• Think in systems and move quickly without sacrificing detail or reliability

Responsibilities

• Python, TypeScript, containers, distributed systems, data tooling, evaluation harnesses, AI agent workflows

Bonus

• Built or led an early-stage company
• Worked on AI evaluations, post-training, model behavior, or simulated environments
• Collaborated directly with frontier model researchers or demanding technical customers
• Built deployment, data, or research infrastructure under rapidly changing requirements

Requirements

• Compensation: $350K to $450K base salary plus meaningful equity
• Location: San Francisco, 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.