Generative AI Developer
Citi•Mississauga, ON
•CA$94,300 - CA$141,500•Onsite
About The Position
We are looking for a skilled Generative AI Developer to join our Controls Technology team and contribute to the development and integration of innovative generative AI solutions. In this role, you'll work closely with senior developers, AI architects, and business stakeholders to build retrieval-grounded, context-aware, and increasingly agentic AI applications that deliver impactful, reliable AI-driven features and products. This role focuses on applying pre-trained and hosted foundation models effectively — through context engineering, RAG, knowledge graphs, and agentic workflows — rather than training or fine-tuning models.
Requirements
- Proficiency in Python for GenAI development, data preprocessing, and scripting.
- Solid understanding of core generative AI concepts — foundation models, LLMs, tokenization, embeddings, and context windows.
- Hands-on experience with prompt engineering and context engineering techniques.
- Experience building RAG systems, including chunking strategies, vector databases, and hybrid search techniques.
- Familiarity with knowledge graphs and an interest in Graph RAG for relationship-aware, multi-hop retrieval.
- Exposure to agentic AI development — building tool-using agents and multi-step workflows with a framework such as Google ADK, LangGraph, CrewAI, or the OpenAI Agents SDK.
- Working knowledge of agent tooling and protocols, including tool/function calling and the Model Context Protocol (MCP); awareness of the A2A protocol for inter-agent communication.
- Understanding of agent harness basics — session/state management, memory, guardrails, and execution controls that make agents reliable.
- Practical experience consuming major GenAI APIs (e.g., OpenAI, Gemini, Claude) and orchestration frameworks such as LangChain and LlamaIndex.
- Understanding of application deployment and containerization (Docker).
- Understanding of version control systems (Git).
- Awareness of AI compliance, data privacy, guardrails, and responsible AI principles.
- Strong teamwork and communication abilities.
- Willingness to learn new AI/GenAI and agentic technologies and frameworks.
- Analytical mindset and attention to detail.
- Openness to feedback and continuous improvement.
- Bachelor's degree or Master's degree in Computer Science, Data Science, AI, or a related field.
- 3–5 years of professional experience in software/AI development, with exposure to Generative AI and agentic AI.
- Experience delivering AI/GenAI projects in a collaborative setting.
Nice To Haves
- Exposure to cloud-based AI/ML environments (AWS, GCP, or Azure) is a plus.
Responsibilities
- Build and integrate generative AI applications using pre-trained and hosted foundation models (via managed GenAI APIs and open-model endpoints).
- Design and implement context engineering workflows — assembling system instructions, retrieved knowledge, tool definitions, conversation memory, and task metadata into reliable, token-efficient prompts.
- Contribute to prompt engineering (zero-shot, few-shot, chain-of-thought, role-based prompting) and the development of AI-powered workflows.
- Develop and maintain Retrieval-Augmented Generation (RAG) systems, including chunking, embedding, hybrid (semantic + keyword) search, and re-ranking.
- Assist with building knowledge graphs and Graph RAG pipelines to support multi-hop reasoning and grounded, traceable responses.
- Contribute to agentic workflows — building AI agents with tool-calling, structured planning, and memory, using frameworks such as Google Agent Development Kit (ADK), LangGraph, or CrewAI.
- Integrate agents with external tools and data sources via the Model Context Protocol (MCP) and enable agent-to-agent collaboration via the Agent2Agent (A2A) protocol under guidance.
- Assist with the deployment, monitoring, and maintenance of GenAI and agentic applications in production environments.
- Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities.
- Perform data preprocessing, document ingestion, and API development for AI applications.
- Participate in code reviews, testing, and documentation to ensure quality and reliability.
- Stay updated with advancements in GenAI and agentic AI and share relevant learnings with the team.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
