Sr AI Engineer

Job summary

Lead emerging technology or enterprise AI initiatives and develop AI solutions using commercial and open-source language models, agentic AI, and Graph/RAG architectures. Build and support full-stack applications and data workflows on AWS, applying SDLC and DevSecOps practices, database optimization, orchestration, and automated testing.

Job details

Pay Range: CAD 70-75/hr In-Person Interview Required • 10 + years of progressive engineering experience. - DO NOT SUBMIT LESS THEN 10 YRS EXP. • 1–2 years of direct experience leading emerging technology or enterprise AI initiatives. • Strong familiarity with the full Software Development Life Cycle (SDLC) best practices and DevSecOps protocols. • Generative AI & LLMs: Core proficiency with commercial and open-source models (GPT, Claude, Gemini, LLaMA), advanced prompt engineering, and LLM fine-tuning techniques. • AI Frameworks & Architectures: Deep hands-on experience with LangChain, LlamaIndex, Amazon Bedrock, Agentic AI, MCP, and Graph/RAG architectures. • Databases & Orchestration: Proven experience with Vector and Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune), query optimization, and ETL orchestration using Apache Airflow/DAGs. • Cloud & DevOps (AWS): Comprehensive knowledge of AWS infrastructure, including computation (EKS, Fargate, Lambda, EC2), networking/load balancing (ELB, GLB, NLB), data analytics (Athena, Glue, Lake Formation), and Infrastructure as Code (Terraform, Puppet, Docker). • Full-Stack Development: Strong proficiency in Python (NumPy, Pandas, Matplotlib, Boto3) alongside modern web application development using Next.js, React, and TypeScript/JavaScript. • Testing & Analytics: Familiarity with automated AI and web testing frameworks (Ragas, Playwright, Zephyr, Selenium) and Business Intelligence tools (QuickSight, Tableau).

What you’ll do

Lead emerging technology or enterprise AI initiatives and develop AI solutions using commercial and open-source language models, agentic AI, and Graph/RAG architectures. Build and support full-stack applications and data workflows on AWS, applying SDLC and DevSecOps practices, database optimization, orchestration, and automated testing.

Requirements

Requires at least 10 years of progressive engineering experience, including 1–2 years leading emerging technology or enterprise AI initiatives. Candidates should have hands-on expertise in LLMs and AI frameworks, AWS infrastructure and DevOps, vector and graph databases, Python and modern web development, and AI and web testing tools.

Listed skills

• prompt engineering · Preferred
• Amazon Web Services · Preferred
• Python · Preferred
• Next.js · Preferred
• React · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Generative AI
• Large Language Models
• Prompt Engineering
• LLM Fine-Tuning
• LangChain
• LlamaIndex
• Amazon Bedrock
• Agentic AI
• Retrieval-Augmented Generation
• Vector and Graph Databases
• Apache Airflow
• AWS
• Python
• Next.js
• React
• DevSecOps

Job areas

• Technology
• Software
• Engineering
• Data & Analytics

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