Job DescriptionYour OpportunityWe are seeking a forward-thinking ML/AI Engineer with a strong foundation in AI and a growing specialization in agentic AI, including both single-agent and multi-agent systems. This role will support our expanding portfolio of AI-driven solutions in the water sector, contributing to a range of projects that involve complex systems, data-driven decision-making, and intelligent automation.
You will collaborate with a cross-functional team of data scientists, engineers, and domain experts to design, prototype, and deploy agentic AI solutions that enhance operational efficiency, system adaptability, and innovation across diverse water-related challenges. You will report to an Innovation Portfolio Manager in Stantec Water BOU's Office of Research, Innovation and Technology.
Key Responsibilities- Design and implement agentic AI systems, including single-agent and multi-agent architectures, for applications in water infrastructure, forecasting, optimizations, and operations.
- Collaborate with ML/AI leads to integrate LLMs and autonomous agents into existing and new solution pipelines.
- Contribute to the development of exploratory prototypes and production-ready tools that leverage agentic reasoning, planning, and collaboration.
- Support the MLOps lifecycle, including model tracking (e.g., MLflow), deployment, and monitoring within Azure DevOps and Databricks environments.
- Translate domain-specific challenges into scalable AI solutions, working closely with water engineers and project teams.
- Stay current with emerging research and tools in Machine Learning, agentic AI, reinforcement learning, and multi-agent systems.
- Document methodologies, share learnings, and contribute to internal knowledge bases and Communities of Practice.
QualificationsQualifications- Master's+ degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
- 5+ years total professional experience, 1+ of hands-on experience in machine learning and AI development, with exposure to agentic AI concepts (e.g., autonomous agents, multi-agent coordination, LLM-based agents).
- Familiarity with LLM frameworks (e.g., LangChain, AutoGen, OpenAI APIs) and multi-agent orchestration tools. Hands-on experience building AI agents with LLMs, including RAG, using these frameworks is preferred.
- Strong programming skills with Python, PyTorch or TensorFlow, and cloud-based ML platforms (preferably Azure). Skills in multiple languages (e.g., Java, Node.js) is a benefit.
- Understanding of MLOps practices, including CI/CD pipelines, model versioning, and monitoring.
- Strong communication skills and ability to collaborate across technical and non-technical teams.
- Experience or interest in water systems, environmental modeling, or Microsoft Azure SDKs such as AI Foundry is a plus.
