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UniSysTech Consulting

Senior AI Developer

Toronto, ON, Canada
Greater Toronto and Hamilton Area, ON, Canada

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Job details

Apply by: Dec 2, 2026
Experience: Advanced AI / ML Expertise: 5+ years of hands-on experience building, training, fine-tuning, and deploying machine learning models and AI applications into production.
Posting language: English
Posted: Nov 2, 2026

Original job description

Position Overview

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

Work Environment

Hybrid Model: Requirement to work 2 days per week in-office at our Downtown Toronto office, with up to 3 days remote flexibility.

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More about this job

Responsibilities

Lead the design, development, and deployment of production-ready AI/ML solutions, including generative AI, RAG architectures, predictive models, and AI-driven backend automations. Build scalable backend APIs and event-driven services, integrate AWS infrastructure, automate MLOps pipelines, and ensure solutions meet enterprise governance, compliance, and security standards.

Requirements

Requires 5+ years of hands-on experience building, training, fine-tuning, and deploying production AI/ML models and applications, along with expertise in LLM orchestration, RAG, vector databases, and prompt engineering. Strong Python backend development and automation experience are essential; practical AWS experience is also sought, while enterprise or regulated-industry experience, responsible AI knowledge, and containerization are advantageous.

Skills

Artificial Intelligence
Machine Learning
Generative AI
Large Language Models
Retrieval-Augmented Generation
LangChain
LlamaIndex
Vector Databases
Prompt Engineering
Python
FastAPI
Backend API Development
AWS
MLOps
CI/CD
Infrastructure as Code

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Generative AI
Large Language Models
Retrieval-Augmented Generation
Predictive Models
LangChain
LlamaIndex
Vector Databases
Prompt Engineering
Python
FastAPI
Flask
Backend APIs
Microservices
AWS Bedrock
Amazon SageMaker
AWS Lambda
Amazon API Gateway
Amazon S3
Amazon ECS
Amazon EventBridge
MLOps
CI/CD
CloudFormation
Terraform
Docker
Kubernetes
Responsible AI

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