Top Senior Level C++ Jobs in Dallas, TX

The Sr. Software Engineer will lead the Card Issuing team at Lithic, focusing on building high reliability APIs and card lifecycle features. Responsibilities include technical leadership, project management, mentoring team members, and continuous improvement of engineering practices.

Senior Backend Engineers at Raya focus on backend engineering in a high-growth environment. Responsibilities include leading core services, enhancing application performance with databases, collaborating with cross-functional teams, and ensuring user-centric development while maintaining operational excellence.

The Integration Engineer will develop, test, and integrate applications using Rust and C/C++. Responsibilities include collaborating with teams to meet integration requirements, debugging and troubleshooting software/hardware, and designing system architecture for varied platforms. The role involves 25% travel for client collaborations and system testing.

The Staff Software Engineer will design, implement, and maintain critical parts of Materialize using Rust, focusing on performance-sensitive distributed systems. Responsibilities include collaborating with engineers and product management to adapt to customer needs and working both autonomously and as part of a team.

This role involves developing scaleout solutions for AI technologies, collaborating with teams to define product offerings, understanding customer needs, and proving out solutions with hardware. Key responsibilities include creating orchestration software and being innovative within cross-functional teams.

The Sr. Software Engineer will design the API platform for products, lead feature development, automate processes, and ensure high-quality backend systems. Role involves collaboration, independent leadership, managing priorities, and working with product requirements.

Lead a team of developers in designing and implementing large language models for Cerence's software products. Collaborate with cross-functional teams to define requirements, create algorithms for model training, and integrate LLM features into voice recognition systems, ensuring high performance and reliability in real-world automotive environments.