Role Description This role is US based remote and all candidates must be able to work in the US now and in the future without restriction. We’re focused on helping private equity investors and portfolio company leaders drive value creation through technology. In a world where investors deploy trillions annually into software and tech-enabled businesses, we're the team that makes sure the underlying technology actually delivers. The expert judgment of our experienced practitioners is complemented by proven frameworks, tech-enabled solutions, and objective data to help organizations navigate critical technology decisions across diligence, transformation, growth, cybersecurity, AI, and operational execution. We’re building small, highly capable engineering pods (2–3 engineers) that own problems end-to-end and move quickly from idea to production. This role is for engineers who are comfortable operating across the full stack and using modern AI-enabled workflows to accelerate delivery. This role is part of our Core Products team, which builds and maintains the tools Crosslake practitioners use to manage assessments and deliver results to clients. You’ll be expected to design, build, and ship software with minimal handoffs—working across frontend, backend, and infrastructure as needed. How we work: - Small teams, high ownership, minimal handoffs - Fast, iterative delivery over heavy process - Pragmatic decision-making over over-engineering - Engineers are expected to operate across the stack, not within silos Key Responsibilities - Design and build full-stack applications from concept to production - Own the full SDLC: design, development, testing, deployment, and iteration - Work within a small pod to deliver quickly with a high degree of autonomy - Contribute to architecture and make pragmatic technical decisions - Use AI tools to accelerate development, testing, and code quality - Iterate rapidly while maintaining a strong bar for reliability and maintainability Qualifications - 7+ years of software engineering experience - Strong full-stack capability (frontend, backend, and cloud infrastructure) - Comfortable stepping into an architectural role when needed - Experience deploying and operating applications in cloud environments (AWS, Azure, or GCP) - Solid understanding of the full SDLC - Deep experience with (i.e., daily usage of) AI coding harnesses - Hands-on experience using AI-assisted development tools beyond basic code generation - Ability to leverage AI across the workflow (e.g., prototyping, debugging, test generation, QA, code review, security analysis) - Familiarity with modern AI-enabled development environments and practices Preferred Experience - Infrastructure as Code (e.g., Terraform) - CI/CD and modern DevOps practices - Extensive experience with one or more of the following languages: Python, Typescript, Golang, Rust - Experience with deploying and maintaining applications in the AWS ecosystem - Experience with AI engineering – building agentic workflows into products that balance efficiency and quality (e.g., Pydantic AI, CrewAI, LangGraph, etc.) What success looks like - You ramp quickly and start contributing within weeks - You ship production-ready features in short cycles - You make sound architectural decisions without overbuilding - You effectively use AI tools to meaningfully increase speed and output