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Senior GenAI Engineer – AWS | LLMs | Agentic AI | RAG Architectures
Job Location:
Monthly Salary:
Experience Required:
Posted:
3 July 2026 (30+ days ago)
Posted:
Application Deadline:
30 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Senior GenAI Engineer AWS LLMs Agentic AI RAG Architectures
Toronto ON Hybrid (23 Days WFO)
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 organizations 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 and DevSecOps protocols.
Experience / Skills
6 years of progressive experience in engineering roles including at least 12 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 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 and Tableau.
Knowledge of financial markets and enterprise data systems.
Required Skills:
60-70
Required Education:
Job Overview:Were seeking an experienced ETL Pipeline Developer proficient in Python to design implement and maintain robust data pipelines. This role is critical for transforming raw data into valuable business insights across our Responsibilities: Architect and build efficient ETL pipelines in Python to process diverse data sources Implement data transformation logic using pandas for complex manipulations and aggregations Document pipeline architecture data flows
