Principal AI Engineer
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Job Description
Senior AI Engineer at Stratus developing generative AI tools and foundation models for MEP contractors. Collaborating with cross-functional teams to optimize engineering workflows and automate tasks.
Responsibilities:
- Build foundation models and generative AI tools alongside a team of technologists.
- Design and build agentic workflows — multi-agent orchestration (e.g., CrewAI, LangGraph, AutoGen), tool use, multi-step planning, and human-in-the-loop checkpoints — to automate complex engineering tasks.
- Establish evaluation, guardrails, and failure-mode analysis for agent systems to ensure they are safe, reliable, and production-ready.
- Develop scalable data pipelines for diverse data sources used in production ML systems, including BIM, CAD, and infrastructure design data.
- Work with large-scale, multi-modal datasets — including text and geometric data — to design novel preprocessing, augmentation, analysis, and content understanding.
- Transform unstructured infrastructure and design data into representations suitable for machine learning.
- Lead cross-functional collaboration with ML Research Scientists and Engineers to align data formats with downstream training and fine-tuning of LLMs.
- Apply deduplication, normalization, and validation techniques to ensure high-quality data in production environments.
- Architect and optimize pipelines for scalability, reproducibility, and cloud deployment.
- Mentor junior engineers and provide technical guidance on complex data challenges.
- Drive technical decision-making and influence best practices across the team.
- Perform requirements analysis with senior stakeholders, ensuring technical solutions meet both immediate project goals and long-term research objectives.
- Communicate findings and technical insights through quantitative analysis, visualizations, and clear documentation.
- Contribute to agile workflows, ensuring flexibility and responsiveness to evolving project needs.
- Participate in technical planning and roadmap development.
Requirements:
- Required MSc or PhD in Computer Science, Engineering, or a related field.
- 5–8+ years of experience in, Engineering, Machine Learning, or related fields.
- Deep programming and software engineering experience strong computer science fundamentals (data structures, algorithms, system design) and a proven track record of shipping and maintaining production-grade code, not just prototypes or notebooks.
- Proven technical leadership in complex projects and guiding technical direction across cross-functional teams.
- Strong experience in geometric data modeling and processing, including complex 2D/3D representations, computational geometry, and data architectures.
- Familiarity with machine learning concepts and frameworks and how data is represented for training.
- Ability to translate research ideas into production-grade systems.
- Excellent communication skills with the ability to influence and guide technical decisions.
Benefits:
- Comprehensive and competitive health benefits plan
- Matching 401k contributions
- 20 days annual PTO
- Primarily remote work with occasional annual team onsites.
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