Principal AI Engineer
$179,000–$226,000 year
HybridTucson, Arizona, United States
Job Summary
Define NOIRLab's enterprise AI strategy, technical vision, and multi-year roadmap aligned with scientific and operational goals. Identify, evaluate, and prioritize high-value AI use cases to deliver measurable impact. Establish engineering standards, reusable frameworks, and governance frameworks ensuring responsible, secure deployment of generative AI, LLMs, and AI agents. Design and implement scalable AI platforms integrating with research systems, while leading the development of RAG systems, AI agents, and copilots. Develop advanced analytics capabilities using machine learning and statistical modeling to support scientific discovery and operational decision-making. Mentor engineers and scientists in AI technologies and architecture, collaborating across scientific, engineering, and operations teams to drive adoption. Engage with external research institutions to promote collaboration and knowledge sharing.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field, or equivalent combination of education and experience
- 15+ years of experience in software engineering, artificial intelligence, machine learning, or related fields, including experience serving as a Principal Engineer, AI Technical Lead, Architect, or equivalent senior technical leadership role
- Demonstrated success designing, building, and deploying production-scale AI and machine learning solutions
- Deep expertise in machine learning, generative AI, large language models, modern AI architectures, and AI engineering best practices
- Experience developing and deploying LLM applications, RAG systems, AI agents, and foundation model-based solutions
- Strong background in cloud-native architecture, distributed systems, data platforms, and AI infrastructure
- Experience implementing AI operationalization practices, including model deployment, monitoring, evaluation, governance, and lifecycle management
- Expertise in secure, responsible AI development and model governance frameworks
- Advanced software engineering skills and proficiency with modern programming languages, frameworks, and AI development ecosystems
- Exceptional communication, leadership, and collaboration skills with the ability to influence diverse technical and non-technical stakeholders
Desired Qualifications
- Experience applying AI, machine learning, or advanced analytics within scientific research environments
- Familiarity with astronomical datasets, observatory operations, scientific instrumentation, or related research domains
- Experience with high-performance computing (HPC), large-scale data processing, or scientific computing platforms
- Contributions to open-source software, AI frameworks, or scientific computing communities
- Experience building organizational AI capabilities and driving enterprise-wide AI adoption strategies
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