Key Responsibilities
Generative AI Engineering & Architecture

Lead the architecture, development, and production deployment of enterprise-grade Generative AI systems with a focus on scalability, reliability, and performance.

Design and implement agentic workflows using LLMs, tools, and orchestration frameworks to enable intelligent autonomous behaviors.

Build and integrate end-to-end GenAI pipelines, including model inference, RAG (Retrieval-Augmented Generation), embeddings, and application consumption via APIs.

Collaborate with data and platform engineering teams to implement vector search, semantic retrieval, and contextual grounding for AI driven responses.

Apply solid full stack engineering skills to build user-facing GenAI applications and robust backend systems.

Develop scalable microservices and secure RESTful APIs to expose AI and ML capabilities across enterprise applications.

Integrate GenAI functions with front-end interfaces built using modern web technologies.

Deployment, Operations, & Quality

Lead model deployment, packaging, performance optimization, and lifecycle management in production environments.

Ensure reliability and quality through test driven development (TDD), reusable component design, and modern architectural principles.

Drive CI/CD based releases, containerized deployments, and DevOps practices for AI-driven applications.

Provide technical mentorship to intermediate engineers and contribute to architectural design reviews.

Champion engineering best practices, coding standards, and continuous improvement within Agile delivery teams.

Required Skills & Technical Expertise
Programming & Full Stack Development





Proficiency in Python, Java, R, and SQL.

Frontend and full stack development experience with ReactJS, HTML, CSS, and Node.js.

AI / ML & Generative AI

Hands-on experience with TensorFlow, Keras, and PyTorch.

Strong foundations in Generative AI, NLP, and NLU.

Expertise working with Large Language Models (LLMs) and prompt engineering.

Agentic & GenAI Frameworks

Experience with LangChain and familiarity with LangGraph and Ollama.

Understanding of agentic system design, tool use, and workflow orchestration patterns.

Retrieval & Knowledge Foundations

Strong knowledge of vector databases, RAG pipelines, semantic search, and embedding techniques.

Demonstrated experience in microservices architecture, service-oriented design, and building scalable REST APIs.

Expertise in API-driven development and integration patterns.

Experience with model packaging, containerization, deployment pipelines, and operational monitoring.

Hands-on experience with GitHub, GitHub Actions, and CI/CD automation.

Familiarity with both SQL and NoSQL databases.

Preferred Qualifications

Experience with cloud-based GenAI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI).

Knowledge of distributed systems, high-availability architectures, and performance tuning.

Prior experience leading technical initiatives or architectural decision-making.

Soft Skills

Strong leadership, communication, and mentoring capabilities.

Ability to work across cross-functional teams in fast-paced Agile environments.

Strategic thinking with the ability to translate business needs into scalable AI solutions.

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📌 Sr. AI Engineer/Gen AI (Ontario)
🏢 Zodiac Solutions
📍 Ontario