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[SX/EIT-MM] Data & AI / AI Agent Engineer Intern
Build and maintain data pipelines and AI applications using Python, LLMs, RAG, and vector databases on Databricks for Generative AI and AI Agents.
Principal Data Scientist
Lead enterprise AI/ML and generative AI initiatives, designing and deploying LLM-based solutions, setting strategic roadmaps, and mentoring teams to drive scalable, secure AI adoption in a large financial services firm.
Forward Deployed Engineer
An AI engineer who collaborates with business teams to identify workflow improvements, design AI-driven solutions (e.g., LLMs, RAG), and ensure deployment, adoption, and measurable business impact—bridging technical execution with stakeholder consulting.
Principal Data Scientist
Lead AI-driven data platform development, designing scalable systems with LLMs, RAG, and multi-agent frameworks to power enterprise intelligence.
Agentic Gen AI Engineer Lead
Lead a team building agentic GenAI systems using LangGraph, LangChain, RAG, and Python for enterprise clients.
Senior AI Developer (Solid experience with AWS, MLOps, AgentCore & GenAI and agentic AI)
Build reusable AI components and agent skills on AWS to accelerate AI adoption across the company, while mentoring engineers and defining standards for GenAI and agentic AI systems.
Principal Artificial Intelligence (AI) Solutions Architect
Principal AI Solutions Architect designs, prototypes, and governs enterprise-scale AI systems, focusing on GenAI (LLMs, RAG, agents) and their integration with business workflows and data pipelines.
ML Engineer, AI Platform (LLMs & Retrieval)
Build AI-driven features using LLMs, RAG, and Agentic AI to enhance Workday’s HR/finance products, deploying scalable ML models and APIs with Python.
Director, AI Solutions Architect
Leads enterprise AI solution design, translating business needs into scalable, secure GenAI and agent-based architectures while aligning with data, security, and governance standards.
Gen AI Solutions Engineer #124
Design and deploy enterprise-scale generative AI agents and RAG pipelines on Google Cloud for SMB and enterprise clients, using Vertex AI, LangChain, and LlamaIndex.
Lead Agentic AI Engineer – VP (Mississauga)
Lead the design and deployment of agentic AI systems for Citi’s banking operations, using Python, Google ADK, LangChain, and LLMs to automate workflows and reduce risk.
Senior AI Engineer, IT Solutions 1
Senior AI Engineer designs and deploys generative AI and RAG systems, scoping solutions, building vector pipelines, and leading MLOps for production-grade AI tools in a manufacturing-focused tech stack.
Senior Applied AI/ML Developer
Build and deploy NLP and ML models to enhance Autodesk’s RAG platforms, leading ML initiatives and mentoring teammates.
Tech Lead Manager, AI / Machine Learning
Lead a small ML team while coding daily to build GenAI features for market research, focusing on agentic systems, NLP tasks, and scalable ML platforms handling millions of requests.
Expert, AI Engineer
Design and deploy enterprise AI solutions, agents, and RAG workflows using Python, SQL, and cloud platforms like Vertex AI and Databricks to automate and enhance CN’s logistics operations.
Senior AI Solution Architect
Design and deliver production-grade GenAI solutions on Azure, integrating LLMs, RAG, and vector databases while leading cross-functional teams and shaping AI strategies.
Generative AI Engineer
Build and deploy next-gen translation engines using LLMs and GenAI, optimizing models for high-stakes legal/financial content while collaborating with ML and DevOps teams.
AI Engineer - Senior Consultant - Toronto
Build and deploy AI/ML solutions for clients, focusing on GenAI, LLMs, and modern cloud platforms to solve complex business problems.
Manager AI Engineer - Python
Lead a Python-based AI engineering team to design, build, and deploy scalable Gen AI solutions using LLMs, RAG, and agentic systems on AWS, while mentoring engineers and driving technical strategy.
Senior AI Engineer - Toronto, ON
Build production-ready GenAI systems using Python, React, and AWS, including LLM pipelines, RAG, and agent-based architectures for scalable AI products.