Job Description
Are you ready to architect the future of intelligent systems?
We are Sentinel Systems, a premier research and development firm pioneering the technological landscape of 2026 and beyond. We are seeking a visionary Lead AI Architect to spearhead our next-generation machine learning infrastructure. In this role, you will define the architectural strategies that will power our solutions for the next decade, bridging the gap between theoretical AI and practical, scalable engineering.
You will work in a high-performance environment, collaborating with top-tier engineers and data scientists to build robust, secure, and scalable AI ecosystems. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and want to leave a lasting impact on the industry, we want to hear from you.
Responsibilities
- Strategic Vision & Roadmap: Define the long-term architectural vision and technical roadmap for AI infrastructure, specifically targeting deployment and capabilities for the year 2026.
- System Design: Design and implement scalable, fault-tolerant, and secure machine learning pipelines and data processing architectures.
- Leadership: Lead a team of senior engineers and data scientists, providing technical mentorship and fostering a culture of innovation and excellence.
- Model Optimization: Oversee the optimization of deep learning models for performance, latency, and resource efficiency.
- Cross-Functional Collaboration: Work closely with product managers, researchers, and stakeholders to translate business requirements into technical specifications.
- Emerging Tech Integration: Evaluate and integrate emerging AI technologies (e.g., quantum computing interfaces, advanced NLP) into existing systems.
Qualifications
- Education: Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 8+ years of experience in software engineering, with at least 5 years in a Lead Architect or Senior Engineering role.
- Technical Skills: Deep expertise in Python, TensorFlow, PyTorch, or similar ML frameworks. Proven experience designing large-scale distributed systems.
- Architecture: Strong understanding of cloud-native architectures (AWS, Azure, GCP) and containerization technologies (Kubernetes, Docker).
- Problem Solving: Demonstrated ability to solve complex technical problems and make high-impact architectural decisions under pressure.
- Communication: Exceptional verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.