Bullseye search · AI Automation Engineer for Law Firms
Most firms still run intake, referrals, scheduling, and document work by hand across tools that don't talk to each other. I run a bullseye search for the engineer who sits with your partners and operations team, builds the automation from zero, and makes the whole firm faster.
The short answer
Chasen Talent is a founder-led recruiting firm that finds AI automation engineers for law firms and legal services for early-stage to growth startups. Founder Chasen Nick runs every search personally as a bullseye search: one specific profile, recruited directly from teams where that work is happening now, and verified before a client ever sees them.
Why I know this role
The right hire doesn't wait for a spec. They shadow your intake team, map where hours disappear, and ship the first automation in weeks. They connect AI models like Claude to your practice management system, documents, and phones through integrations such as MCP, then keep a human in the loop where accuracy and privilege matter. I screen for engineers who have done exactly that for a business, and who can show the hours they saved.
The target
Has wired AI models into real business tools through APIs and integrations like MCP, with Claude or similar models doing real work, not demos.
Has built lead capture, conflict checks, routing, and referral partner tracking so no new matter falls through the cracks.
Has shipped AI voice agents or call workflows for intake, scheduling, and follow up, with transcripts flowing into your systems.
Has migrated a business off spreadsheets, on premise servers, or aging software without losing data or stopping work.
Works directly with partners and operations staff, scopes the problem, and owns the build end to end as the first or only engineer.
Treats confidentiality, privilege, access control, and audit trails as part of the design, and knows when a person must review the output.
Has automated drafting, extraction, or review of real documents like intake forms, letters, and pleadings.
Ties every build to time saved, matters handled, or revenue, not to how clever the tech is.
Where I find them: Automation and AI engineers at legal tech companies, engineers who built internal tools for law firms, insurance, healthcare, or other regulated service businesses, founding engineers from workflow automation startups, and solutions engineers who now want to own the build.
How a bullseye search works
We pin down the exact profile together: what they've shipped, the stack, the stage, and the dealbreakers. No keyword lists.
I map who's doing this work right now and recruit them directly with your specific role. Most of them are not applying anywhere.
I check real track record and current role before anyone reaches you, so you meet finalists, not a stack of resumes.
Every step is run by me, Chasen Nick. No handoffs to junior recruiters. How that compares to a big agency →
Questions founders ask
They find the manual work that eats attorney and staff time, such as intake, referral tracking, scheduling, calls, and document drafting, and replace it with automation. That usually means connecting AI models to the firm's practice management system, email, documents, and phones, then keeping a person in the loop where accuracy matters.
MCP (Model Context Protocol) is an open standard for connecting AI models like Claude to the tools and data a business already uses. For a law firm, it lets an assistant work safely with your matters, calendars, and documents instead of living in a separate chat window.
Buy when an off the shelf tool fits your workflow. Hire when your edge lives in your own intake, referral relationships, or process and no product reaches it. Most firms end up doing both, with the engineer connecting and extending the tools they buy.
Proof they have automated a real business workflow end to end, comfort working directly with non engineers, sound judgment on client data and privilege, and the ability to ship something useful in the first month. Experience in a regulated industry matters more than experience at a big AI lab.
California, New York, and remote across the United States. Most searches on my desk right now are in-person roles in San Francisco.
Other bullseye searches
Tell me about the role. If I'm not the right fit for it, I'll tell you that too.
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