Senior AI Engineer to design, build, and productionize secure agentic AI ; RAG, MCP, multi agents
Listed on 2026-10-08
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Software Development
AI Engineer (Applied/Software), Backend Developer, Machine Learning/ ML Engineer
Our financial services client is seeking a Senior AI Engineer (10+ years) to design, build, and product ionize secure agentic AI applications using RAG, MCP servers, and multi-step reasoning workflows
Join a leading Canadian digital banking environment delivering agentic AI initiatives focused on scalable, production-grade applications. This role supports the development of LLM-powered systems including retrieval-augmented generation (RAG), structured outputs, MCP servers, and secure microservices. The position works closely with product, data, engineering, platform, and security stakeholders to deliver enterprise AI capabilities. Current initiatives focus on safe agent development, platform scalability, and production-ready AI engineering.
MustHaves
- 10+ years building production-grade Python applications using Scikit-learn, Pandas, Num Py, and Matplotlib/Seaborn
- Hands-on delivery of LLM-powered applications including RAG, agents, structured outputs, and prompt safety
- Production experience building and consuming MCP servers including endpoints, schemas, and access boundaries
- Production implementation of OAuth 2.0, OpenID Connect, and SAML within microservices and API authentication environments
- Education in computer science, engineering, data science, or a related field
- Experience with Agentic AI frameworks and multi-step AI reasoning processes
- Experience with MLOps tools including Git, Docker, and CI/CD for machine learning models
- Experience building NLP, IVR, or contact center intelligence applications
- Familiarity with Google Vertex AI
- Finance or banking industry experience
- Design and product ionize LLM-powered and agentic AI applications
- Build and consume MCP servers with defined schemas, endpoints, and access boundaries
- Develop secure, low-latency services and microservices with authentication and authorization controls
- Partner with product, data, engineering, platform, and security stakeholders to deliver AI capabilities
- Ensure systems are testable, observable, resilient, and supported by automated testing
- Contribute to architectural discussions and evolving AI development practices
- Mentor peers through code reviews and design discussions
Our financial services client is seeking a Senior AI Engineer (10+ years) to design, build, and product ionize secure agentic AI applications using RAG, MCP servers, and multi-step reasoning workflows
Join a leading Canadian digital banking environment delivering agentic AI initiatives focused on scalable, production-grade applications. This role supports the development of LLM-powered systems including retrieval-augmented generation (RAG), structured outputs, MCP servers, and secure microservices. The position works closely with product, data, engineering, platform, and security stakeholders to deliver enterprise AI capabilities. Current initiatives focus on safe agent development, platform scalability, and production-ready AI engineering.
MustHaves
- 10+ years building production-grade Python applications using Scikit-learn, Pandas, Num Py, and Matplotlib/Seaborn
- Hands-on delivery of LLM-powered applications including RAG, agents, structured outputs, and prompt safety
- Production experience building and consuming MCP servers including endpoints, schemas, and access boundaries
- Production implementation of OAuth 2.0, OpenID Connect, and SAML within microservices and API authentication environments
- Education in computer science, engineering, data science, or a related field
- Experience with Agentic AI frameworks and multi-step AI reasoning processes
- Experience with MLOps tools including Git, Docker, and CI/CD for machine learning models
- Experience building NLP, IVR, or contact center intelligence applications
- Familiarity with Google Vertex AI
- Finance or banking industry experience
- Design and product ionize LLM-powered and agentic AI applications
- Build and consume MCP servers with defined schemas, endpoints, and access boundaries
- Develop secure, low-latency services and microservices with authentication and authorization controls
- Partner with product, data, engineering, platform, and security stakeholders to deliver AI capabilities
- Ensure systems are testable, observable, resilient, and supported by automated testing
- Contribute to architectural discussions and evolving AI development practices
- Mentor peers through code…
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