AI Engineer

Job summary

Design, develop, and deploy scalable generative AI solutions on AWS, including RAG systems, fine-tuned LLMs, and multi-step agent workflows. Integrate AI models with enterprise systems, optimize performance and cost, and follow MLOps practices for deployment, monitoring, security, and governance.

Job details

Job Requirements EIM Senior AI Engineer Location: PCS CA~TORONTO Years of Experience: 10-15 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. Follow MLOps best practices for model deployment, monitoring, and governance. Ensure security, scalability, and reliability of AI platforms and services. Mandatory Skills Strong in Python and SQL (Advanced Level: 7 to 10 Years) AWS Bedrock AWS SageMaker LLM fine-tuning LangGraph RAG (Retrieval-Augmented Generation) Preferred Skills AWS Certifications (AWS Certified Machine Learning, AWS Solutions Architect, or related certifications) Qualifications Experience in AI Engineering is a deal breaker. Candidates should possess a strong background in AI technologies and demonstrate the ability to deliver high-quality AI solutions in a collaborative environment. Work Experience 10-15Years

What you’ll do

Design, develop, and deploy scalable generative AI solutions on AWS, including RAG systems, fine-tuned LLMs, and multi-step agent workflows. Integrate AI models with enterprise systems, optimize performance and cost, and follow MLOps practices for deployment, monitoring, security, and governance.

Requirements

Requires 10–15 years of AI engineering experience and advanced Python and SQL skills, with 7–10 years specified for those programming skills. Mandatory expertise includes AWS Bedrock, AWS SageMaker, LLM fine-tuning, LangGraph, and RAG; relevant AWS certifications are preferred.

Listed skills

• Python · Preferred
• SQL · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• AWS Bedrock
• AWS SageMaker
• LLM Fine-Tuning
• LangGraph
• Retrieval-Augmented Generation
• Generative AI
• AI Engineering
• Data Pipelines
• MLOps
• Model Deployment
• Model Monitoring
• AI Agents

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Consulting

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