We are seeking an experienced Senior AI Developer to lead the design, development, and deployment of enterprise-grade Artificial Intelligence and Machine Learning solutions. In this role, you will focus on building intelligent back-end systems, automated workflows, and scalable AI capabilities. While experience with cloud automation in AWS is highly valuable, deep AI/ML expertise is the primary priority for this role.

We are looking for an engineer who excels at utilizing modern AI frameworks, LLMs, and intelligent automation to solve complex back-end problems.

AI & Machine Learning Engineering: Lead the design and implementation of production-ready AI/ML capabilities, including Generative AI models, Retrieval-Augmented Generation (RAG) architectures, and predictive solutions. Build automated back-end pipelines and processes that leverage AI to optimize operational workflows, data processing, and enterprise tooling.

AWS Integration & Cloud Infrastructure: Work closely with AWS services (e.SageMaker, Bedrock, Lambda, EventBridge) to host, automate, and scale AI-driven backend services.

MLOps & Pipeline Automation: Implement automated CI/CD workflows for model deployment, monitoring, model drift tracking, and continuous integration/delivery.

Technical Leadership & Architecture: Partner with enterprise architects, data engineers,



and security teams to ensure AI systems align with governance, compliance, and enterprise risk standards.

Advanced AI / ML Expertise: 5+ years of hands-on experience building, training, fine-tuning, and deploying machine learning models and AI applications into production.

Generative AI & Up-to-date AI Frameworks: Proficiency with LLM orchestration (e.LangChain, LlamaIndex), RAG pipeline design, vector databases, and prompt engineering. Strong proficiency in Python (FastAPI, Flask, or async Python frameworks) and software design patterns focused entirely on backend services, APIs, and data processing. Demonstrated experience automating complex backend tasks, data pipelines, and system workflows using AI-driven approaches.

AWS & Cloud Skills (Secondary Focus) AWS Cloud Services: Practical experience with core AWS backend and AI infrastructure, such as AWS Bedrock, SageMaker, Lambda, API Gateway, S3, ECS, and EventBridge.

Infrastructure as Code & DevOps: Exposure to CloudFormation or Terraform, alongside standard Git-based CI/CD pipelines. Knowledge of Responsible AI principles, model governance, and data security standards. Typescript, React, Angular and Java Hybrid Model: Requirement to work 2 days per week in-office at our Downtown Toronto office, with up to 3 days remote flexibility. #

📌 Senior Ai Developer (Toronto)
🏢 Unisystech Consulting
📍 Toronto