Software Engineer

Location

Dogpatch, San Francisco, CA / Meatpacking District, New York, NY

Fully onsite, 5 days per week.

Company Stage of Funding

Early-Stage / High-Growth AI Infrastructure Company

Office Type

On-site — 5 days per week

Candidates should be comfortable working fully in-office in either San Francisco or New York City.

Salary

$170,000 – $240,000 Base

Equity

Competitive Equity

Visa

Visa transfers considered. No new visa sponsorship.

Experience

1–5 years of experience in full-stack software engineering.

Employment Type

Full-time

Hiring Count

Early / Growth Hiring

Company Description

This is a fast-growing AI data infrastructure company building the next generation of infrastructure for leading AI labs.

The company sources, processes, and delivers high-value training data that does not exist on the open internet, including expert-produced financial documents, medical materials, scientific write-ups, legal materials, and other proprietary artifacts that are critical for developing frontier AI systems.

The company operates at the intersection of AI infrastructure, data acquisition, full-stack software engineering, and real-world operational workflows.

Its core product is an end-to-end data acquisition and processing pipeline that works directly with professionals and institutions holding proprietary information. The platform processes these artifacts through sophisticated anonymization and redaction systems before they enter datasets, enabling AI labs to access rich domain-specific data while maintaining strict standards around confidentiality and security.

The company is still early-stage, with approximately 30 employees, but already works with leading AI labs on important capability areas including computer use, finance, multimodal generation, and enterprise productivity.

This role joins a small, high-impact team building a new business line from the ground up. The team operates like a founding unit, with direct access to senior leadership and significant responsibility for shaping the product, engineering processes, and direction of the business.

The ideal candidate is a high-slope full-stack engineer and generalist who enjoys owning problems end-to-end, shipping quickly, working directly with internal users, and using modern AI coding tools to dramatically increase their development velocity.

This is not a narrow engineering role. Engineers are expected to work closely with operations, understand the problems those teams face, determine what needs to be built, make pragmatic product decisions, and personally take features from idea through production.

What You Will Do

1. Work Closely With Operations & Internal Users

• Partner directly with operations teams to identify bottlenecks, inefficiencies, and opportunities for automation.
• Talk directly with internal users to understand their workflows and pain points.
• Translate operational problems into practical software solutions.
• Build tools that give operators significant leverage.
• Iterate quickly based on real-world user feedback.
• Identify opportunities to automate repetitive or manual processes.
• Work closely with business and operations stakeholders to understand what the product needs to accomplish.
• Balance user needs, engineering effort, and business impact when deciding what to build.
• Take ownership of problems rather than waiting for fully defined requirements.

2. Own Full-Stack Features End-to-End

• Own features across the full software development lifecycle.
• Build full-stack applications using TypeScript from front-end through back-end.
• Take features from initial idea and requirements through implementation, testing, and deployment.
• Personally write production-quality code.
• Ship features quickly, often in days rather than weeks.
• Work across different parts of the stack depending on the problem.
• Build internal and customer-facing workflows that support the company's data infrastructure business.
• Debug and improve existing systems as the product evolves.
• Make pragmatic engineering and product tradeoffs.
• Contribute across the entire product rather than operating within a narrowly defined technical area.

3. Use AI Coding Tools To Multiply Engineering Impact

• Use modern AI coding tools such as Cursor and Copilot as part of the everyday development workflow.
• Leverage AI tools to accelerate implementation, debugging, refactoring, and exploration.
• Critically evaluate AI-generated code rather than blindly accepting suggestions.
• Understand when AI-generated implementations are incorrect, inefficient, insecure, or poorly designed.
• Use AI tools to rapidly prototype and test ideas.
• Develop strong workflows for combining AI-assisted development with sound engineering judgment.
• Continuously experiment with new AI development tools and techniques.
• Maintain high standards for code quality while operating at a significantly accelerated development pace.

4. Operate As a High-Slope Generalist

• Pick up whatever technical problem is most important to the business at a given time.
• Work across front-end, back-end, data, integrations, and internal tooling as required.
• Operate effectively in an environment where priorities can change rapidly.
• Make independent technical decisions with limited direction.
• Contribute to a small founding-style engineering team.
• Work directly with senior leadership and company founders.
• Help build new products and business lines from the ground up.
• Take ownership of ambiguous problems and turn them into working solutions.
• Contribute beyond strictly defined engineering responsibilities when the business requires it.
• Help shape engineering practices, product direction, and team culture as the company scales.

Ideal Candidate Background

Experience Requirements

• 1–5 years of full-stack software engineering experience.
• Experience building and shipping production software.
• Experience owning features end-to-end.
• Experience working across both front-end and back-end systems.
• Experience working in fast-moving product environments.
• Experience operating with significant technical autonomy.
• Experience translating loosely defined problems into working software.
• Experience collaborating directly with internal users or business stakeholders.
• Experience working in startups or other high-growth environments is strongly preferred.
• Experience working on small engineering teams is highly valuable.
• Experience taking ownership of projects from concept through production.
• Demonstrated ability to learn new technologies quickly and work outside a narrowly defined specialty.

Technical Requirements

• Strong full-stack software engineering fundamentals.
• Strong TypeScript experience.
• Experience building both front-end and back-end applications.
• Experience developing production web applications.
• Strong understanding of APIs and application architecture.
• Experience working with modern web development frameworks and tooling.
• Ability to debug complex application issues.
• Strong understanding of software engineering fundamentals including:
  • Data structures and algorithms
  • APIs
  • Application architecture
  • Testing
  • Debugging
  • Version control
  • Deployment
• Ability to write clean, maintainable production code.
• Comfortable learning unfamiliar technologies quickly.
• Experience using modern developer tooling.
• Strong preference for candidates who have experience working across the full stack rather than specializing exclusively in either front-end or back-end development.

AI Coding & Product Engineering Requirements

• Fluency with modern AI coding tools such as Cursor, Copilot, or similar tools.
• Demonstrated ability to use AI coding assistants to accelerate development.
• Strong judgment when reviewing AI-generated code.
• Ability to identify incorrect assumptions, bugs, security issues, and poor architectural decisions in AI-generated output.
• Experience rapidly prototyping software using AI-assisted development workflows.
• Interest in the evolution of AI-native software development.
• Comfortable balancing development velocity with engineering quality.
• Strong product engineering instincts.
• Ability to determine what should be built rather than simply implementing predefined specifications.

Product & Operations Requirements

• Experience building software for internal users, operators, or business teams is a strong plus.
• Strong product sense and ability to understand user workflows.
• Experience gathering requirements directly from users.
• Ability to identify high-leverage automation opportunities.
• Comfortable working closely with operations teams.
• Ability to make pragmatic product and engineering tradeoffs.
• Strong understanding of how software can improve operational efficiency.
• Comfortable working in environments where requirements are continuously evolving.
• Experience building tools that automate manual or operational workflows is highly valuable.

Soft Skills

• High ownership and accountability.
• Strong autonomy.
• Entrepreneurial mindset.
• High learning velocity.
• Strong problem-solving ability.
• Comfortable with ambiguity.
• Highly adaptable.
• Strong product intuition.
• Pragmatic decision-making.
• Excellent written and verbal communication.
• Comfortable working directly with users.
• Comfortable operating in a small team.
• Willingness to take on unfamiliar problems.
• Strong bias toward action.
• Comfortable moving quickly.
• Strong attention to detail.
• Able to balance speed and quality.
• Motivated by visible, high-impact work.

Compensation & Benefits

• $170,000 – $240,000 base salary.
• Competitive equity.
• Fully onsite, 5 days per week.
• San Francisco or New York City location.
• Opportunity to join a small, high-impact engineering team.
• Significant ownership over product development.
• Opportunity to work directly with senior leadership and founders.
• Exposure to AI infrastructure and frontier AI applications.
• Opportunity to use cutting-edge AI coding tools as part of everyday engineering.
• Ability to shape a new business line from an early stage.
• High-autonomy environment with significant visibility and impact.

Why Join

• Join an early engineering team building a new business line from the ground up.
• Work directly with senior leadership and company founders.
• Own full-stack features from idea through production.
• Work closely with operations teams and directly observe the impact of what you build.
• Build software that creates significant leverage for internal users.
• Work on next-generation AI data infrastructure.
• Build systems supporting leading AI labs and frontier AI development.
• Use AI coding tools to dramatically increase engineering velocity.
• Operate as a high-slope generalist rather than being limited to a narrow engineering function.
• Have significant influence over product decisions and technical direction.
• Work in an environment where engineers ship in days rather than weeks.
• Help shape engineering culture and processes as the company grows.
• Take on high-impact problems across product, engineering, operations, and data infrastructure.