- Salary
- $60 – $70
- Location
- TORONTO
- Workplace
- Hybrid, Onsite
- Type
- Contract
- Department
- Engineering
- Source
- PCRecruiter
Description
Sr AI Engineer
This is with a global IT services firm for a very large investment fund with global reach.
Location: downtown Toronto, near TTC and GO Train
Hybrid work - 4 days in office/week
Contract - 6 months, possible renewal
Rate: $60 to 70hr B2B
Project description
We are looking for an experienced AI Engineer to design and deliver scalable Gen AI solutions. The role involves building production-ready AI products using Python, React, and AWS, while leveraging modern architectures such as LLM pipelines, RAG, and agent-based systems.
Responsibilities
AI Engineer Responsibilities
Lead and actively contribute to the development of AI products, pilots and solutions, with a focus on clean, maintainable code using Python, React, and AWS tools.
Design, architect and build scalable Gen AI solutions, including LLM pipelines, Agentic, MCP, Graph/RAG architectures, and prompt-based applications and emerging tech.
Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.
Optimize performance of AI products, Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains.
Work closely with product managers, data scientists, and domain experts to define technical solutions aligned with business needs.
Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization's AI roadmap.
Own end-to-end delivery of Gen AI solutions. Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban).
Monitor operational metrics and incident data to drive continuous improvement and reliability.
Ensure adherence to governance, DevSecOps protocols.
Must have Experience/Skills:
6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives.
Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques
Agentic AI, MCP, and Graph/RAG architectures
Gen AI Framework (LangChain, LlamaIndex, Amazon Bedrock)
Web application development using Next.js, React, TypeScript/JavaScript
AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation)
Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments
ETL orchestration using Apache Airflow/DAGs
Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization
Python programming (NumPy, Pandas, Matplotlib, Boto3)
Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium,)
Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).
Knowledge of LLM fine tuning techniques
Experience in BI tools like QuickSight, Tableau
Nice to have
Knowledge of financial markets, capital markets, and enterprise data systems
NOTE:
G.G. Consulting Group uses advanced ATS systems to track and manage candidates and jobs. We do not use AI tools for candidate screening.
This is with a global IT services firm for a very large investment fund with global reach.
Location: downtown Toronto, near TTC and GO Train
Hybrid work - 4 days in office/week
Contract - 6 months, possible renewal
Rate: $60 to 70hr B2B
Project description
We are looking for an experienced AI Engineer to design and deliver scalable Gen AI solutions. The role involves building production-ready AI products using Python, React, and AWS, while leveraging modern architectures such as LLM pipelines, RAG, and agent-based systems.
Responsibilities
AI Engineer Responsibilities
Lead and actively contribute to the development of AI products, pilots and solutions, with a focus on clean, maintainable code using Python, React, and AWS tools.
Design, architect and build scalable Gen AI solutions, including LLM pipelines, Agentic, MCP, Graph/RAG architectures, and prompt-based applications and emerging tech.
Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.
Optimize performance of AI products, Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains.
Work closely with product managers, data scientists, and domain experts to define technical solutions aligned with business needs.
Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization's AI roadmap.
Own end-to-end delivery of Gen AI solutions. Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban).
Monitor operational metrics and incident data to drive continuous improvement and reliability.
Ensure adherence to governance, DevSecOps protocols.
Must have Experience/Skills:
6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives.
Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques
Agentic AI, MCP, and Graph/RAG architectures
Gen AI Framework (LangChain, LlamaIndex, Amazon Bedrock)
Web application development using Next.js, React, TypeScript/JavaScript
AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation)
Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments
ETL orchestration using Apache Airflow/DAGs
Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization
Python programming (NumPy, Pandas, Matplotlib, Boto3)
Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium,)
Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).
Knowledge of LLM fine tuning techniques
Experience in BI tools like QuickSight, Tableau
Nice to have
Knowledge of financial markets, capital markets, and enterprise data systems
NOTE:
G.G. Consulting Group uses advanced ATS systems to track and manage candidates and jobs. We do not use AI tools for candidate screening.
Skills
PythonJavaScriptTypeScriptReactNext.jsAWSDockerTerraformPandasNumPyAirflowETLJiraConfluenceTableauAgileScrumKanban
