Senior Software Engineer, Crosslake Technologies

• This role is for engineers who are comfortable operating across the stack while bringing strong backend and systems design expertise
• 7+ years of software engineering experience
• Strong backend expertise with the ability to operate across the full stack when needed
• Experience designing service-oriented or distributed systems
• Familiarity with domain-driven design (DDD) principles
• Exceptional systems thinking and ability to model complex domains
• 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 tools
• 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)
• Ability to balance AI-assisted development with sound system design and long-term maintainability
• Familiarity with modern AI-enabled development environments and practices

Desirable

• 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 part of our Services team, which builds the shared backend services and system foundations that power many of Crosslake’s tools and products
• These systems are designed for reuse, scalability, and long-term maintainability
• This role requires strong architectural thinking and hands-on execution, with a focus on building reliable, extensible services that support multiple use cases over time
• Design and build shared backend services and APIs used across multiple systems
• Define service boundaries, contracts, and data models
• Own the full SDLC: design, development, testing, deployment, and iteration
• Contribute to domain modeling and system design decisions
• Ensure services are scalable, reliable, and reusable
• Improve system cohesion and reduce duplication across tools and products
• Use AI tools to accelerate development while maintaining high code quality
• Balance speed with long-term maintainability and extensibility
• How we work:
• Small teams, high ownership, minimal handoffs
• Fast, iterative delivery with an emphasis on sound system design
• Pragmatic decision-making over over-engineering
• Engineers are expected to operate across the stack, not within silos
• What success looks like:
• You design services that are reused across multiple systems
• You create clean abstractions that simplify downstream development
• You balance speed with long-term maintainability
• You improve system consistency and reduce fragmentation
• You effectively use AI tools to increase speed without sacrificing quality