Join our team as a Software Development Engineer (SDE) and technical lead, where you'll design, build, and maintain an AWS cloud-based Requirements Management Software that streamlines how cross-functional teams create, track, and validate product requirements throughout the hardware development lifecycle. This Software will serve as the backbone for managing business requirements, product requirements, test cases, and verification & validation (V&V) results — enabling full traceability from concept to production across device programs.
Key job responsibilities
As the SDE on this project, you'll own the end-to-end development of a scalable, secure, and highly available web application on AWS, leveraging AI technologies to deliver intelligent features such as automated requirement analysis, smart traceability, and AI-assisted workflows. You'll serve as the technical lead for a team of SDEs — driving project execution, setting technical direction, conducting code reviews, and mentoring engineers to grow their skills. You'll also engage directly with end users and stakeholders to gather, clarify, and refine software requirements, ensuring the tool meets real-world needs across diverse functional teams.- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience building complex software systems that have been successfully delivered to customers
- Experience debugging, profiling, and implementing best software engineering practices in large-scale systems
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
- Experience as a mentor, tech lead or leading an engineering team
- Experience with AWS or other cloud technologies.- 5+ years of full stack development experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Knowledge of consumer electronic product develop process
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