Technical Architect with GenAI
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Job Location:
Mississauga - Canada
Monthly Salary:
Not Disclosed
Posted on:
5 hours ago
Vacancies:
1 Vacancy
Job Summary
Role: Technical Architect with GenAI
Location: Mississauga ON
Contract
We are seeking a forward-thinking Java Technical Architect with 10 years of experience to lead enterprise modernization initiatives with deep integration of Generative AI (GenAI) capabilities. The ideal candidate will combine strong Java expertise with hands-on experience in Python LLM frameworks Agentic architectures and RAG pipelines while driving scalable solutions through modern DevOps and cloud-native practices.
Location: Mississauga ON
Contract
We are seeking a forward-thinking Java Technical Architect with 10 years of experience to lead enterprise modernization initiatives with deep integration of Generative AI (GenAI) capabilities. The ideal candidate will combine strong Java expertise with hands-on experience in Python LLM frameworks Agentic architectures and RAG pipelines while driving scalable solutions through modern DevOps and cloud-native practices.
Key Responsibilities
Architect and lead modernization of legacy systems using Java and Python integrating GenAI capabilities.
Design and implement LLM-powered solutions using tools like LangChain Semantic Kernel Hugging Face and OpenAI API.
Build and optimize RAG pipelines for enterprise-grade retrieval and generation workflows.
Apply prompt engineering techniques to enhance model performance and reliability.
Develop Agentic systems using frameworks such as AutoGen CrewAI or custom agents.
Drive DevOps practices including CI/CD containerization and infrastructure-as-code.
Deploy scalable secure solutions on AWS Azure or GCP.
Utilize productivity tools like GitHub Copilot ChatGPT and Gemini to accelerate development.
Collaborate with cross-functional teams to align GenAI strategy with business goals.
Mentor engineering teams on GenAI adoption coding best practices and architectural standards
Architect and lead modernization of legacy systems using Java and Python integrating GenAI capabilities.
Design and implement LLM-powered solutions using tools like LangChain Semantic Kernel Hugging Face and OpenAI API.
Build and optimize RAG pipelines for enterprise-grade retrieval and generation workflows.
Apply prompt engineering techniques to enhance model performance and reliability.
Develop Agentic systems using frameworks such as AutoGen CrewAI or custom agents.
Drive DevOps practices including CI/CD containerization and infrastructure-as-code.
Deploy scalable secure solutions on AWS Azure or GCP.
Utilize productivity tools like GitHub Copilot ChatGPT and Gemini to accelerate development.
Collaborate with cross-functional teams to align GenAI strategy with business goals.
Mentor engineering teams on GenAI adoption coding best practices and architectural standards
Key Skills
- APIs
- SOAP
- Software Architecture
- .NET
- Design Patterns
- Enterprise Software
- AWS
- Solution Architecture
- Cloud Architecture
- Java
- SSO
- Oracle
