Product Lead
Location: Hybrid — remote with regular time in our Santa Monica office
Reports to: CEO, collaborates with Engineering, AI, and Legal
Comp: $125K–$175K + meaningful early-stage equity + unlimited PTO
About Inhouse
Inhouse builds AI tools that help small businesses handle legal work faster and more affordably.
We pair custom AI with our own law firm to deliver fast, compliant legal work at a fraction of the cost and turnaround of traditional firms. That lawyer supervision improves our AI accuracy over time, ensuring our system is reliable irrespective of the user’s prompting skills.
We’ve handled over 6 million legal chats to date. After 1,500% revenue growth, we recently raised a $5M seed led by top VCs and the former CEO & cofounder of LegalZoom.
The Role
We’re not looking for a traditional product manager. We’re looking for an operator or engineer in the legal industry who has already built AI-driven workflows and wants to turn that experience into a consumer product for SMBs.
You’ve spent the last few years building agentic tools inside a law firm or legal tech company. Maybe your title was legal ops, legal engineer, or product manager. You understand both the latest AI platforms and the existing legal tech stack. You’ve built systems that handle real workflows — not just experiments.
You may or may not be a lawyer, but can play one on TV.
Now you want to apply that experience to a product already serving hundreds of thousands of SMBs and consumers.
As the Product Lead, you’ll help refine our vision, define the roadmap, and prototype with real users. You’ll sit at the intersection of AI, engineering, design, data, and legal — and be responsible for improving the quality and usefulness of what we ship.
What You’ll Do
Upgrade our legal workflows into a legal operating system
We’ve built lightweight, specialized agents and workflows across the consumer legal space–think intake agents, contract drafters and escalation points. Now we want to make them proactive and more robust. This is where you’ll draw from your experience deploying agents in a law firm or legal tech company. You’ll research and meticulously document the desired behavior, prototype it with users, and work with engineering to bring it to life.
Own the prompt library
Work with our lawyers to write, test, and iterate on prompts and system instructions for drafting and reviewing contracts — NDAs, service agreements, employment docs, shareholder agreements, leases. Treat prompts like production code: versioned, tested, and continuously improved.
Talk to users and shape the product
Interview customers, analyze usage, and prototype quickly. Write PRDs and work with design and engineering to ship and refine features. Co-own the roadmap and be accountable for improving accuracy and making the product more useful over time.
Build eval infrastructure with engineering
Worth with our AI team to define how we measure quality: issue spotting, risk grading, redline quality, clarity of explanations, and jurisdictional nuance. Curate strong datasets. Use them to benchmark models, catch regressions, and validate improvements.
Who You Are
You’ve built and deployed AI systems for legal workflows that real users rely on.
- You designed or owned a system that handled intake, drafting, review, routing, or escalation
- You wrote or led the prompts and system architecture
- You’ve iterated based on real feedback, not just internal testing
You understand both:
- how legal work actually gets done
- how current AI systems behave in practice
You’re familiar with tools like Harvey, Legora, Spellbook, etc., and have strong opinions on what they do well and where they fall short.
You move quickly and prototype using no-code or lightweight tools. You stay current with new models and adapt as they change.
You want to step into a broader product role. This means:
- working closely with engineers and designers
- owning decisions and outcomes
- bringing structure to ambiguous problems
Nice to Have
- Practicing lawyer
- Active in the legal tech community
- Prior PM experience
- Experience managing or mentoring others
Not a Fit
- Lawyers who want to move into tech but haven’t built real systems
- Career PMs without hands-on experience building AI workflows
- People who prefer well-defined problems over ambiguity