Principal AI Engineer

Stratus

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.

Posted 6/18/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Comprehensive and competitive health benefits plan
Matching 401k contributions
20 days annual PTO
Primarily remote work with occasional annual team onsites.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

foundation modelsgenerative AI toolsmulti-agent orchestrationdata pipelinesmachine learningdata normalizationdata validationcloud deploymentgeometric data modelingproduction-grade code

Soft Skills

technical leadershipcross-functional collaborationmentoringcommunicationinfluencingrequirements analysistechnical decision-makingagile workflowsflexibilityresponsiveness

Certifications

MSc in Computer SciencePhD in Computer ScienceMSc in EngineeringPhD in Engineering