Staff Software Engineer

Location

Financial District, San Francisco, CA

Company Stage of Funding

Seed Stage
Total Funding: Approximately $29M+

Office Type

Hybrid — 3 days per week in the San Francisco office, usually Monday through Wednesday.

Office Address: 601 California Street, Financial District, San Francisco, CA.

Salary

$290,000–$340,000 USD annually.

Bonus

25% annual performance bonus.

Equity

Competitive equity.

Visa

Open to visa transfers, including OPT and H-1B transfers. New visa sponsorship availability has not been confirmed.

Relocation

Relocation support available.

Employment Type

Full-time

Hiring Count

Not specified.

Company Description

This company is building an AI-powered platform for private markets investors, including private credit, private equity, and commercial banking professionals.

The platform transforms dense, unstructured deal materials—including data rooms, due diligence documents, financial statements, and other financial information—into auditable, investment-grade analysis and polished investment memos. It helps finance teams accelerate diligence, underwriting, and portfolio monitoring, with customers reporting that they can evaluate deals more than 60% faster.

The product is designed specifically for finance professionals and incorporates AI agents that generate investment memos and finance-grade presentations, collaboration tools, and memory of previous work so that teams can build on earlier analysis.

The company is already trusted across thousands of deals, with customers including major commercial banks and private credit funds. Its customers include Jefferies and Golub Capital, with Golub Capital also serving as an investor.

Backed by NFX, Left Lane Capital, Y Combinator, and other investors, the company has raised more than $29M across its pre-seed and seed rounds. Founded in 2025, it has approximately 35 employees and is experiencing strong commercial growth.

The company operates across New York, San Francisco, and London, with a lean, flat organizational structure and a strong emphasis on AI-native engineering.

What You Will Do

1. Own Large Product Areas End to End

• Take ownership of major product areas across the full stack, including frontend, backend, and database migrations.

• Build and improve core AI-powered product workflows used by private markets investors and finance teams.

• Own significant product initiatives from initial technical design through implementation, deployment, and iteration.

• Build complex AI-powered features, including agents that generate investment-grade presentations and financial memos.

• Make architectural and technical decisions that influence the direction of major product areas.

• Balance speed of execution with reliability, maintainability, and product quality.

2. Build AI-Native Software Using Coding Agents

• Use AI coding agents as a core part of day-to-day engineering work.

• Build, modify, review, and maintain code using AI agents rather than relying primarily on manual coding.

• Use AI tools throughout the development lifecycle, including implementation, debugging, testing, and code review.

• Review and validate AI-generated code to ensure quality, correctness, and maintainability.

• Continuously improve engineering workflows through effective use of AI tools.

• Help establish best practices for AI-native software development across the engineering team.

3. Drive Technical Architecture and Engineering Quality

• Write technical design documents independently for major engineering initiatives.

• Set a high bar for system architecture, code quality, and engineering practices.

• Review technical designs and code from other engineers, spending approximately 10–20% of time on these responsibilities.

• Identify architectural improvements and technical risks before they become larger problems.

• Establish engineering standards that support the company's rapid product and customer growth.

• Help other engineers make better technical decisions and improve their execution.

4. Act as a Technical Force Multiplier

• Raise the technical bar across the engineering team through mentorship, feedback, and hands-on collaboration.

• Make other senior and staff engineers more effective through strong technical judgment and design reviews.

• Lead major product pillars or infrastructure initiatives with measurable business and engineering impact.

• Help engineers improve their system design, implementation quality, and overall execution.

• Establish patterns and practices that enable a small engineering team to deliver more.

• Influence engineering direction without relying on formal management authority.

5. Build Customer-Focused Product Solutions

• Work directly with customers, sales, customer success, and product teams.

• Understand the workflows and requirements of finance professionals working in private credit, private equity, and commercial banking.

• Translate complex customer problems into practical technical solutions.

• Build features that improve diligence, underwriting, investment analysis, and portfolio monitoring.

• Participate in customer conversations and use feedback to guide product development.

• Take ownership of delivering features that create measurable customer value.

6. Partner With a Small, Senior Engineering Team

• Work closely with the engineering lead, CTO, and other engineers in a flat organizational structure.

• Collaborate across frontend, backend, database, and AI-powered product development.

• Take initiative rather than waiting for detailed requirements or predefined tasks.

• Share technical context and help establish strong engineering practices as the team grows.

• Contribute hands-on while also improving the effectiveness of the broader engineering organization.

• Help the company scale its engineering capabilities alongside its growing commercial momentum.

Ideal Candidate Background

Experience Requirements

• 8+ years of software engineering experience; 7 years is the absolute minimum.

• Strong background as a full-stack software engineer or Member of Technical Staff at a Seed to Series E startup.

• Clear career progression, with evidence of promotions and increasing responsibility.

• Experience owning a major product area, product pillar, or large infrastructure initiative end to end.

• Proven ability to influence engineering quality and make other engineers more effective.

• Strong engineering background, ideally combining experience at Big Tech companies and early-stage startups.

• Experience working in a small, senior engineering team with high ownership and limited management layers.

• A clear and specific reason for wanting to join an early-stage startup.

Candidates should have a degree in Computer Science or a related engineering discipline, including Computer Engineering, Electrical Engineering, or Mechanical Engineering. Bootcamp-only backgrounds and unrelated academic backgrounds are not preferred.

Technical Requirements

Programming and Full-Stack Engineering

• Strong software engineering fundamentals.

• Experience working across frontend, backend, and database layers.

• Ability to own full-stack product development independently.

• Experience with backend development using Python.

• Comfortable working across different parts of a product rather than specializing narrowly in one layer.

• Experience with database design, migrations, and application architecture.

AI-Native Engineering

• Uses AI coding agents regularly as part of day-to-day engineering work.

• Has experience building and shipping software with AI coding agents.

• Understands how to review, debug, test, and validate AI-generated code.

• Comfortable delegating implementation work to AI agents while maintaining engineering ownership.

• Can explain how AI tools have changed their development workflow and productivity.

• Demonstrates a genuinely AI-native approach rather than occasional use of autocomplete or basic AI assistance.

System Design and Architecture

• Experience designing and owning large product areas or complex infrastructure projects.

• Can independently write technical design documents.

• Strong understanding of architecture, scalability, maintainability, and system reliability.

• Can evaluate technical trade-offs and communicate design decisions clearly.

• Experience reviewing architecture and technical decisions made by other senior engineers.

• Able to identify and address technical debt and engineering bottlenecks.

Product Engineering

• Experience building customer-facing software products.

• Ability to work across the full product lifecycle, from understanding customer needs to shipping features.

• Experience working with product managers, customers, sales, or customer success teams.

• Strong ability to translate ambiguous business requirements into technical solutions.

• Comfortable building features that involve complex workflows and business logic.

Python

• Experience with Python as part of the engineering stack.

• Ability to contribute to backend and full-stack product development.

• The supplied role information lists Python as the tech stack; other specific frontend frameworks, databases, and infrastructure technologies have not been confirmed.

Ownership and Execution

• Has led a major product pillar or infrastructure project from conception through delivery.

• Can demonstrate measurable impact from projects they have owned.

• Takes responsibility for technical decisions and outcomes.

• Comfortable operating independently with limited management oversight.

• Can balance hands-on implementation with broader technical leadership.

• Proactively identifies problems and opportunities rather than waiting for direction.

• Can move quickly without compromising engineering quality.

• Has a clear track record of increasing scope and responsibility.

Technical Leadership and Mentorship

• Has made other senior and staff engineers better through technical guidance and collaboration.

• Can review complex technical designs and identify architectural risks.

• Provides meaningful feedback on code quality and engineering practices.

• Helps establish technical standards across the engineering team.

• Can influence engineering direction without requiring a formal management role.

• Has experience acting as a technical leader while remaining hands-on.

Collaboration and Communication

• Comfortable working directly with customers and understanding their business needs.

• Can communicate technical concepts to non-engineering stakeholders.

• Works effectively with sales, customer success, product, and engineering teams.

• Can explain technical trade-offs and design decisions clearly.

• Comfortable working in a flat, fast-moving startup environment.

• Takes initiative and communicates proactively.

• Enjoys collaborating with a small, senior engineering team.

Nice-to-Have Qualifications

• Experience at both Big Tech and an early-stage startup.

• Experience at a Seed to Series E company.

• Experience building AI-powered products or agentic workflows.

• Experience with coding agents and AI-native development tools.

• Experience building products for financial services, private credit, private equity, commercial banking, or investment teams.

• Experience with document-heavy workflows, financial analysis, or enterprise software.

• Experience building products involving complex data processing and unstructured documents.

• Experience working directly with enterprise customers.

• Experience mentoring senior and staff-level engineers.

• Experience scaling engineering practices within a small team.

Compensation & Benefits

• Base salary of $290,000–$340,000 USD annually.

• 25% annual performance bonus.

• Competitive equity.

• Relocation support.

• Full-time position.

• Hybrid work arrangement, with 3 days per week in the San Francisco office, usually Monday through Wednesday.

• Visa transfers supported, including OPT and H-1B transfers.

Why Join

• Own major parts of an AI-powered platform used by private markets investors and commercial banking professionals.

• Build customer-facing AI products that turn complex financial documents into investment-grade analysis.

• Work in a small engineering team where individual contributions have a significant impact.

• Help shape the architecture, technical direction, and engineering practices of a growing company.

• Work in an AI-native environment where coding agents are central to how software is built and reviewed.

• Partner directly with customers and influence product decisions.

• Take on a Staff-level role with meaningful technical leadership and end-to-end ownership.

• Help scale engineering capabilities as the company's revenue and customer base grow.

• Join a company with strong commercial traction, more than $29M in funding, and established financial-services customers.