AI Developer (LLM & Agentic Systems)

WSP•Toronto, ON

16h•Remote

About The Position

As an AI Developer (LLM & Agentic Systems), you will design and develop AI-enabled applications and intelligent systems used in client-facing projects, supporting decision-making across mining, resources, infrastructure, and environmental domains. You will build next-generation AI applications that combine Large Language Models (LLMs), structured data, and domain knowledge to enable advanced reasoning and support complex engineering and operational decisions. This role can be based anywhere in Canada and plays a key part in advancing our AI‑enabled platforms, internal tooling, and next‑generation data solutions.

Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related discipline.
5+ years of professional software development experience, including 2+ years leading the design, deployment, and scaling of LLM-based or agentic AI systems in production environments.
Demonstrated experience designing end-to-end AI architectures, including data ingestion, retrieval, reasoning layers, and user-facing applications.
Strong experience with LLM workflows, including prompt engineering, evaluation strategies, agent orchestration, and tool integration.
Hands-on experience with embeddings, vector search, and RAG pipelines, including performance optimization and retrieval quality improvements.
Proven ability to design and build scalable backend systems and APIs (Python – FastAPI preferred, or Node.js), including microservices architectures.
Experience integrating structured and unstructured data into scalable AI applications.
Experience applying NLP techniques (e.g., entity extraction, entity resolution) in real-world applications.
Strong experience with cloud-native development (Azure preferred), including deployment, monitoring, and cost/performance optimization.
Experience with DevOps practices, including CI/CD pipelines, Git workflows, and multi-environment deployments (dev, UAT, production).

Nice To Haves

Experience with knowledge graphs and graph query languages (e.g., SPARQL, Cypher)
Experience with microservices
Experience with Docker/Kubernetes
Experience with ETL pipelines
Experience with engineering‑heavy data environments

Responsibilities

Design, build, and maintain scalable full‑stack applications that integrate advanced AI and data capabilities.
Develop backend APIs and cloud‑native components that support scalable data and analytics workflows.
Integrate LLMs, agentic workflows, and NLP techniques (e.g., entity recognition and entity resolution) into production-ready systems.
Contribute to the design and evolution of knowledge‑based and data‑driven platforms.
Develop and integrate data pipelines and knowledge-driven components (e.g., structured data, semantic layers, or knowledge graphs) into applications.
Collaborate closely with analytics, data science, knowledge engineering, and digital product teams.
Work directly with internal teams and clients to translate requirements into scalable, production-ready solutions.
Implement secure, maintainable, and testable code aligned with industry best practices.
Support CI/CD, Git workflows, and DevOps automation.