Senior Staff Engineer, Software
Skills
About the Role
You will be a foundational pillar of the strategy in the Content portfolio, injecting deep expertise into the product portfolio. Your mission is to research, architect, and pioneer solutions that process and extract intelligent insights from millions of unstructured documents and multi-media files every day. This is a founding engineer opportunity where you'll be one of the primary authorities responsible for identifying and implementing state-of-the-art techniques for document ingestion, classification, entity extraction, image search, and more. You'll research, evaluate, and prototype cutting-edge solutions using Large Language Models, Computer Vision, and other techniques to solve complex data extraction challenges. You'll design and build robust, scalable, cost-effective AI services and data processing pipelines that form the backbone for processing millions of documents daily with high reliability and throughput. You'll go beyond theory to solve practical production AI problems, including managing LLM latency and variance, developing prompt engineering strategies, and building fault-tolerant, defensive systems. You'll also act as a key technical mentor and thought leader for the engineering team, driving mission-critical initiatives to production.
Requirements
- 10+ years of professional software engineering experience building complex, data-intensive, backend systems
- 5+ years deep expertise in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Spring Boot or similar
- Mastery in designing large-scale distributed systems, including asynchronous patterns, streaming/queuing/caching strategies, and observability
- Exceptional communication and leadership skills with ability to influence engineering direction across multiple teams without direct authority
- Hands-on experience in the complete lifecycle of AI/ML models (nice to have)
- Proficiency with modern DevOps and MLOps practices including CI/CD, Infrastructure as Code, automated testing (nice to have)
- Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes (nice to have)
Responsibilities
- Research, evaluate, and prototype cutting-edge solutions using Large Language Models, Computer Vision, and other techniques
- Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines
- Manage LLM latency and variance and develop sophisticated prompt engineering strategies
- Build fault-tolerant, defensive systems that perform consistently
- Act as key technical mentor and thought leader for the engineering team
- Drive mission-critical initiatives to production