AI Engineer
- Toronto, ON, Canada
Full-time
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Job details
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Original job description
Job Requirements
AI Engineer
Location: PCS CA~TORONTO
Years of Experience: 7-10 Years
Job Summary: We are seeking a highly skilled AI Engineer with strong expertise in Python, SQL, AWS Bedrock, AWS SageMaker, LangGraph, LLM Fine-Tuning, and Retrieval-Augmented Generation (RAG). The ideal candidate will be responsible for designing, developing, and deploying scalable AI/GenAI solutions, building intelligent agents, fine-tuning Large Language Models (LLMs), and implementing enterprise-grade AI applications on AWS.
Responsibilities
Proven track record of delivering AI solutions in a collaborative environment, with a focus on continuous improvement and operational excellence.
Work Experience
7-10Years
AI Engineer
Location: PCS CA~TORONTO
Years of Experience: 7-10 Years
Job Summary: We are seeking a highly skilled AI Engineer with strong expertise in Python, SQL, AWS Bedrock, AWS SageMaker, LangGraph, LLM Fine-Tuning, and Retrieval-Augmented Generation (RAG). The ideal candidate will be responsible for designing, developing, and deploying scalable AI/GenAI solutions, building intelligent agents, fine-tuning Large Language Models (LLMs), and implementing enterprise-grade AI applications on AWS.
Responsibilities
- Design, develop, and deploy Generative AI solutions using AWS services.
- Build and optimize AI applications leveraging AWS Bedrock and AWS SageMaker.
- Develop and maintain scalable data pipelines using Python and SQL.
- Implement and enhance Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge retrieval and question-answering systems.
- Fine-tune open-source and foundation LLMs to improve domain-specific performance and accuracy.
- Design and orchestrate multi-step AI workflows using LangGraph and agent-based frameworks.
- Integrate AI models with enterprise applications, APIs, databases, and cloud services.
- Evaluate, monitor, and optimize AI model performance, latency, and cost.
- Collaborate with business stakeholders, architects, and engineering teams to translate requirements into AI-driven solutions.
- 8+ years of software engineering, platform engineering, or DevOps experience with strong software development experience in Python.
- Deep expertise with Kubernetes and Amazon EKS.
- Strong hands-on experience with Terraform, ArgoCD, and Jenkins.
- Experience with AWS networking concepts including VPC, Route Tables, Security Groups, Load Balancers, DNS, IAM.
- Experience working with containers and container orchestration platforms.
- AWS Certifications (AWS Certified Machine Learning, AWS Solutions Architect, or related certifications).
- Some experience with KDBx, Nvidia NIMs, Grafana would be a bonus.
Proven track record of delivering AI solutions in a collaborative environment, with a focus on continuous improvement and operational excellence.
Work Experience
7-10Years
More about this job
Responsibilities
Design, develop, and deploy scalable generative AI solutions on AWS, including RAG systems, fine-tuned language models, and agent workflows. Integrate AI with enterprise systems and data pipelines, and evaluate and optimize model performance, latency, and cost in collaboration with stakeholders and engineering teams.
Requirements
The posting seeks 7–10 years of experience and emphasizes Python software development, Kubernetes and Amazon EKS, Terraform, Argo CD, Jenkins, containers, and AWS networking. It also calls for hands-on expertise with AWS Bedrock, SageMaker, LangGraph, LLM fine-tuning, and RAG; AWS certifications are preferred, and KDBx, Nvidia NIMs, or Grafana are bonuses.
Skills
- Python
- SQL
- AWS Bedrock
- AWS SageMaker
- LangGraph
- Large Language Model Fine-Tuning
- Retrieval-Augmented Generation
- Kubernetes
- Amazon EKS
- Terraform
- Argo CD
- Jenkins
- AWS Networking
- Container Orchestration
- AI Agent Development
- Data Pipelines
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
Keywords
- Artificial Intelligence
- Generative AI
- Python
- SQL
- AWS Bedrock
- AWS SageMaker
- LangGraph
- Large Language Models
- LLM Fine-Tuning
- Retrieval-Augmented Generation
- RAG
- AI Agents
- Kubernetes
- Amazon EKS
- Terraform
- Argo CD
- Jenkins
- AWS Networking
- Virtual Private Cloud
- Route Tables
- Security Groups
- Load Balancers
- DNS
- IAM
- Containers
- Container Orchestration
- Data Pipelines
- AWS Certifications
- Nvidia NIMs
- Grafana