GenAI Engineer

Role

Title:

AI Engineer (Generative AI)

Location:

Toronto, ON

Skills:

Digital :
Kubernetes~AI & Gen AI - Products & Tools
Experience

Required:

10 & Above

Role Overview
The AI Engineer will contribute to the development and enhancement of Generative AI capabilities within enterprise applications. Working alongside senior engineers, this role is responsible for implementing agentic workflows, building backend services, integrating LLM based features, and supporting Retrieval Augmented Generation (RAG) systems. The ideal candidate has strong programming foundations, hands on experience with Python, and growing expertise in modern GenAI frameworks.
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Key Responsibilities

• Develop and enhance Generative AI features within enterprise grade applications under the guidance of senior engineers.

• Implement agentic workflows, prompt based solutions, and LLM integrations using established frameworks and cloud based AI services.

• Build and integrate backend services and REST APIs to support GenAI features across platforms.

• Support RAG implementations, including embedding generation, vector database integration, and contextual data retrieval.

• Assist in model inference, evaluation, and continuous improvement of AI outputs.

• Contribute to full stack GenAI applications, including backend logic and basic frontend integration.

• Follow modern engineering best practices—code reviews, test driven development (TDD), CI/CD pipelines, and secure coding standards.

• Collaborate within Agile teams, participate in sprint ceremonies, and continuously develop expertise in emerging GenAI technologies.
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Required

Skills & Qualifications

Programming & Engineering

• Hands on experience with Python.

• Working knowledge of Java, R, and SQL.

• Basic frontend skills:
React

JS, HTML, CSS.

• Understanding of REST APIs and microservices fundamentals.

AI / ML Foundations

• Exposure to Tensor Flow, Keras, or PyTorch.

• Strong understanding of Generative AI fundamentals, NLP, and NLU concepts.

• Familiarity with LLMs, their usage patterns, and basic prompt engineering techniques.

Generative AI & Frameworks

• Experience with Lang Chain; familiarity with Lang Graph and Ollama is an asset.

• Understanding of vector databases, embeddings, and RAG architectures.

Model Deployment

• Basic knowledge of model packaging, inference pipelines, and deployment workflows.
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Preferred Qualifications (Nice to Have)

• Exposure to cloud AI services (Azure OpenAI, AWS Bedrock, Google Vertex AI).

• Understanding of agentic LLM patterns or workflow orchestration.

• Experience contributing to end to end GenAI prototype applications.
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Soft Skills

• Strong collaboration and communication skills.

• Curiosity and willingness to learn emerging GenAI technologies.

• Ability to work in cross functional, fast paced Agile environment