Technology

Long Lake; New York, San Francisco (NY, CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Long Lake is transforming the services economy with AI. We build operating systems for real businesses, deploying AI to production and iterating until it becomes indispensable.

As part of the team, you will design, deploy, and improve AI-driven workflows across portfolio companies, turning complex data tasks into reliable, repeatable processes with measurable impact.

Responsibilities

• Design and deploy production-grade AI systems that operators rely on daily.
• Embed with portfolio companies to run discovery, ship vertical tools, and automate workflows.
• Build deployment infrastructure to make AI adoption repeatable across new workflows.
• Collaborate on expanding adoption beyond early power users and measure impact.

Job description

We are transforming the services economy with AI.
Long Lake acquires service business and transforms how they operate through a shared AI platform, forward-deployed engineers, and a world-class M&A / operations team.

We're backed by General Catalyst, Alpha Wave, Elad Gil, and others, with billions in permanent capital raised. We are not a private equity fund but a permanent capital vehicle with an extremely long-term view.

The Role

Most AI companies build demos. We build and run operating systems for real businesses. This is a rare chance to own the full arc: design the system, deploy it into production, watch operators rely on it every day, and iterate until it's irreplaceable.

What You’ll Do

Some engineers at Long Lake focus on our AI platform: agent orchestration, real-world evals, connectors, data infrastructure. Others spend more time embedded with portfolio companies, running discovery, shipping vertical tools, automating workflows and driving adoption.

Problems you might work on:

• Turning a workflow where someone spends hours copying data between systems, QA-ing outputs, and producing documents into a background agent that runs in minutes and flags exceptions for review
• Writing the integration between a modern agent and a legacy industry ERP with no clean API, and making it reliable enough to run core business operations
• Building the deployment infrastructure that makes rolling AI into a new business repeatable rather than bespoke: the orchestration, connectors, and reliability layer that every new workflow inherits
• Going onsite with a team, expanding adoption beyond the early power users, measuring impact, and shipping the changes that make daily use feel obvious
• Building the evals, feedback loops, and training pipelines that teach AI to reliably complete specific jobs, turning capable models into genuine AI coworkers

What Success Looks Like

• You've shipped something into daily production use, not a pilot or a proof of concept, and the team would notice if it went down tomorrow
• A workflow that used to take a person hours now runs as a background agent, and the hours have been redirected to higher-leverage work
• Something you built once has been reused across multiple portfolio companies, because you designed for the second deployment, not just the first
• You can point to a specific business metric (throughput, cycle time, error rate) that moved because of work you led

Equal Opportunity
Long Lake is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any.