Senior AI Developer

Unisystech Consulting Inc.; Toronto; Hybrid; CAD 140,000 - 180,000; Full time

Job summary

Unisystech Consulting Inc. seeks a Senior AI Developer to lead the design, development, and deployment of enterprise AI/ML solutions. Focus on building intelligent back-end systems, automated workflows, and scalable AI capabilities.

The role emphasizes deep AI/ML expertise with strong Python backend skills and experience with modern AI frameworks, LLM orchestration, and MLOps. Hybrid model with 2 days in-office at our Downtown Toronto office, plus remote flexibility.

Qualifications

• 5+ years hands-on experience building, training, and deploying ML models into production.
• Proficiency with Generative AI, LLM orchestration, and modern AI frameworks.
• Strong Python skills (FastAPI/Flask/async) and backend design patterns.
• Experience automating complex backend tasks and data pipelines using AI-driven approaches.

Responsibilities

• Lead design and implementation of production-ready AI/ML capabilities, including Generative AI models and RAG architectures.
• Build automated back-end pipelines and processes leveraging AI to optimize workflows and data processing.
• Collaborate with AWS services (SageMaker, Bedrock, Lambda, EventBridge) to host and scale AI-driven backend services.
• Architect robust, secure back-end APIs and microservices; ensure performance and reliability.
• Implement CI/CD for model deployment, monitoring, and drift tracking (MLOps).
• Partner with enterprise architects, data engineers, and security teams to meet governance and risk standards.

Skills

Advanced AI/ML

Generative AI

Python

Back-End APIs

Automation engineering

Tools

LangChain

LlamaIndex

Job description

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.

Key Responsibilities

• 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.
• Intelligent Automations: 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.g., SageMaker, Bedrock, Lambda, EventBridge) to host, automate, and scale AI-driven backend services.
• Back-End API & Service Development: Architect robust, secure, and performant back-end APIs, microservices, and asynchronous event-driven systems.
• 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.

Qualifications & Key Requirements

Must-Have Skills (Top Priority)

• 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 & Modern AI Frameworks: Proficiency with LLM orchestration (e.g., LangChain, LlamaIndex), RAG pipeline design, vector databases, and prompt engineering.
• Back-End Mastery: Strong proficiency in Python (FastAPI, Flask, or async Python frameworks) and software design patterns focused entirely on backend services, APIs, and data processing.
• Automation Engineering: 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.

Nice-to-Have Skills

• Background in large enterprise or regulated industries (e.g., Financial Services, Telecommunications).
• Knowledge of Responsible AI principles, model governance, and data security standards.
• Familiarity with containerization (Docker, Kubernetes/EKS).
• 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.