Software Engineer Jobs in Frisco, TX

Lead the technical architecture and hands-on implementation of a cross-platform desktop app for Windows and macOS. Make framework, packaging, IPC, and auto-update decisions; implement core features (file integrations, notifications, clipboard, system tray); integrate with backend agent and AI services (streaming, auth); define engineering standards, testing, and performance benchmarks; and mentor/join a greenfield desktop engineering team while partnering with Product and Design.

As a Lead Software Engineer, you will design AI-driven backend systems for accounting, integrating LLMs, ensuring performance and security, and collaborating with teams on AI solutions.

The Principal Engineer will design scalable backend services and APIs, optimize performance, and improve developer experience while collaborating with AI/ML experts and legal specialists.

As a Staff Software Engineer, you'll design scalable backend services, oversee architecture decisions, optimize performance, and enhance CI/CD processes while collaborating with teams.

The Staff Software Engineer will lead the design and implementation of the ingestion and indexing pipeline for a search platform, ensuring operational health and scalability while leveraging distributed systems and AI technology.

Lead architecture and implementation of AI-first backend and orchestration systems for Audit Suite. Drive scalable, reliable AI workflows (LLM integration, retrieval, vector stores), mentor engineers, set technical direction, and collaborate across product, design, and ML to deliver auditable, high-throughput document-centric solutions.

As a Senior Software Engineer, Full Stack, you will build backend services and APIs for a document analysis platform, focusing on server-side architecture and data processing, while also contributing to frontend features as needed.

The Staff Software Engineer will lead technical initiatives, ensure application integrity, mentor junior engineers, and contribute to software development in a distributed environment.

Design, build, and deploy production-grade legal AI solutions by translating legal user needs into robust software. Collaborate with AI engineers, apply prompt/LLM evaluation, use DevOps and Infrastructure-as-Code, practice TDD, mentor junior engineers, lead agile projects, and deliver end-to-end solutions for law firms and legal departments.

Lead the design and delivery of AI solutions for legal professionals. Mentor engineers, establish AI engineering practices, and ensure scalable architecture and quality across systems.