About this role
Rockstar is recruiting for an AI implementation firm built for private equity. They partner with PE firms managing $10B+ in AUM to deploy AI across portfolio companies in healthcare, education, and financial services. They are profitable, growing fast, and operate with a lean team that punches well above its weight. They own the full lifecycle from strategy through production deployment.
The firm's view is that AI has fundamentally changed what one great engineer with business judgment can accomplish. They are built around that. Rather than staffing large teams, they hire a small number of exceptional people, give them real ownership over client engagements, and pay them based on outcomes and speed. Compensation is uncapped and tied directly to the profit generated on the work an individual leads — every engagement has a P&L, and the people who do the work share in the upside. Quarterly, in cash, fully transparent.
The RoleThe candidate will be building AI systems that go into production for real businesses. They will work directly alongside the founding team and senior engineers on client engagements, owning pieces of the technical build from day one.
They will learn fast because they are close to everything: the client problem, the architecture decisions, the deployment, and the business outcome. They will see how AI actually gets adopted inside companies and what makes the difference between a demo and something that changes how a business operates.
The best engineers grow into leading engagements, owning client relationships, and building teams. That path moves quickly at a small firm growing fast, and the people who show up early have a fundamentally different trajectory.
What You'll DoBuild AI systems end-to-end: LLM integrations, workflow automation, data pipelines, and custom toolingShip production code for client engagements in healthcare, education, and financial servicesWork with senior team members to translate business requirements into technical implementationsIterate on deployed systems based on real-world performance and client feedbackResearch and evaluate emerging AI tools against actual client needsContribute to internal engineering standards, tooling, and documentation as they scale
What We're Looking For1-3+ years of experience in software engineering or applied AIStrong fundamentals in Python and comfort picking up new tools quicklySome hands-on experience with LLMs, whether through work, side projects, or hackathonsThe candidate has shipped something real that people actually usedBias toward figuring things out rather than waiting to be told what to doCurious about the business side (the candidate wants to understand why they are building something, not just how)Bonus: experience with RAG, agents, orchestration frameworks, or data pipelinesBonus: exposure to healthcare, education, or professional services
CompensationBase salary: $135,000-$175,000Profit share participation on engagements the candidate contributes to, scaling as their role growsClear path to AI Deployment Lead ($200K+ base, 25-30% engagement profit share) based on ability to own delivery independentlyFull visibility into engagement P&Ls from day one