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About the job Software Engineer
Job Description
Job Title: Software Engineer (Full-Stack)
Location: On-site in San Francisco, CA
Industry: LegalTech / AI / SaaS
Job Type: Full-Time (Direct Hire)
Salary Range: $120,000 - $250,000/year
Equity: 0.15% - 1.5%
Relocation Package: Available for qualified candidates
Visa Sponsorship: Available for qualified candidates
Hiring Count: 1
Overview:
Lawson Enterprises is partnering with a fast-growing, YC-backed LegalTech startup to hire a highly skilled Software Engineer for a full-time, direct hire opportunity. This company is building AI-powered agents that automate corporate transactions for elite law firms, supporting $3-6 trillion in annual deal flow.
This is a high-impact, high-ownership role within a lean, elite team where engineers ship production code daily and directly influence product direction. The ideal candidate is a strong full-stack engineer who thrives in fast-paced environments and enjoys solving complex technical problems at scale.
Why Join This Opportunity:
Join a well-funded startup backed by Y Combinator with strong early traction and multi-million dollar contracts signed within the first year.
Work directly with a cofounder who is a top partner at one of the largest global law firms.
Be part of a lean, high-performing team with zero bureaucracy and immediate impact.
Receive full budget for AI tools, experimentation, and development resources.
Build technology that is transforming how corporate legal transactions are executed.
Key Responsibilities:
Full-Stack Development & Ownership:
Build end-to-end features and products with a high degree of ownership and autonomy.
Ship production-ready code quickly in a fast-paced startup environment.
Architecture & Infrastructure:
Work on core architectural and infrastructure challenges to support an AI-driven platform.
Design scalable systems that handle large volumes of structured and unstructured data.
AI & Data Pipelines:
Design and build pipelines for document ingestion, extraction, and analysis across large-scale legal datasets.
Develop systems that process and interpret complex documents with high accuracy.
Agentic Workflows & Automation:
Architect multi-step AI workflows that reason across hundreds of documents to generate structured, actionable outputs.
Continuously improve system performance and automation capabilities.
Cross-Functional Collaboration:
Work directly with senior M&A lawyers and partners to understand workflows and translate them into automated systems.
Collaborate closely with a small, high-performing engineering team.
Required Qualifications:
4+ years of experience in full-stack software engineering.
Strong experience building and shipping production-level features.
Proficiency in Python and Next.js.
Experience designing scalable systems and working with complex architectures.
Ability to take ownership of problems and execute with minimal oversight.
Strong problem-solving and critical thinking skills.
Preferred Qualifications:
Experience at a high-growth startup or in a high-impact role within an established company.
Background in regulated industries such as LegalTech or FinTech.
Experience working with AI/ML systems or data-intensive applications.
Familiarity with document processing, NLP, or workflow automation systems.
Tech Stack:
Python
Next.js
Compensation & Benefits:
Salary: $120,000 - $250,000/year
Equity: 0.15% - 1.5%
Relocation Support: Available for qualified candidates
Full budget for AI tools and experimentation
High-growth environment with direct impact on product and business outcomes
Interview Process:

1. Screening interview with Steph, Founder & CEO (30 minutes)
2. Technical assessment (30-45 minutes)
3. On-site team culture interview (1-2 hours)
4. Work trial

1. Company Type: YC-backed startup with strong funding and rapid growth
2. Team Size: ~6 employees (lean, high-impact team)
3. Work Policy: 5 days in-office in San Francisco
4. Industry Focus: AI-powered automation for corporate legal transactions
5. Work Style: Fast-paced, collaborative environment with daily product releases