Staff AI Engineer to serve as technical lead for agentic AI and LLM-powered solutions, owning delivery from concept through production while aligning stakeholders, dependencies, and platform standards, for a digital banking client. Is this role right for you? In this role, you will: Deliver and Scale Agentic AI Solutions:

- Serve as the technical lead and primary engineering point person for AI use cases within the focus
- area, owning technical decomposition, delivery coordination, dependency management, and execution
- quality from concept through production
- Build partnerships with business domains to demonstrate the art of possible and translate business
- requirements to delivery timelines and features.
- Design, build, and productionize LLM-powered and agentic applications, including retrievalaugmented
- generation (RAG), multi-step reasoning workflows, structured outputs, and prompt safety.
- Work hands-on to de-risk complex problems by writing, reviewing, and operating production-grade
- AI systems.

Architect

Secure, Reliable, and Observable Systems:

- Align use case design with platform patterns, governance expectations, and operational support
- Ensure systems are testable, observable, and resilient, with automated testing and clear operational
- feedback loops.
- Design and operate secure, low-latency services and microservices with modern authentication and
- authorization.
- Contribute to architectural discussions, platform capabilities, and evolving best practices for AI
- development.
- Collaborate with platform, security, and risk partners to ensure systems meet enterprise compliance,
- operational, and governance standards.

Influence Technical

Direction and Engineering Culture - Take ambiguous problems and translate them into clear technical solutions, communicating trade-offs

- and constraints.
- Model a culture of engineering excellence, inclusion, and continuous learning — digging into root
- causes and sharing durable lessons.
- Influence technical direction beyond the immediate team by contributing reusable patterns,
- engineering standards, and architectural guidance across AI initiatives.
- Mentor peers through code reviews and design discussions, raising the bar for quality, ownership, and
- long-term thinking.

Required Qualifications

- Experience leading complex AI initiatives across multiple stakeholders from business case through
- production rollout
- Ability to make sound technical trade-offs across speed, risk, scalability, and maintainability
- Experience in AI safety, evaluation, and responsible AI practices.
- Strong communicator with the ability to manage relationships, align stakeholders, and navigate
- dependencies across projects and products
- Extensive experience in Python and its core data science libraries (e.g., Scikit-learn, Pandas, NumPy,
- Matplotlib/Seaborn).
- Hands-on experience building LLM-powered applications — retrieval, agents, structured outputs,
- prompt safety.
- Strong experience in full stack fundamentals and microservices.



Production experience with API
- authentication and authorization (OAuth 2.0, OpenID Connect, and SAML) is required.
- Deep understanding of structured and unstructured data management and their corresponding
- technologies.
- Proven experience in automated testing, including unit and functional testing, and the ability to
- develop test strategies and design automation frameworks.

Preferred Qualifications

- Served as tech lead for an AI driven product and established partnership with product management
- Experience with Agentic AI frameworks and designing multi-step AI reasoning processes
- Experience with MLOps principles and tools for model versioning (e.g., Git), containerization (e.g.,
- Docker), and continuous integration/continuous deployment (CI/CD) of machine learning models
- Strong theoretical and practical knowledge of classical machine learning algorithms (e.g.,
- classification, regression, clustering, dimensionality reduction) and their applications in areas such as
- fraud detection, credit risk scoring, or customer segmentation
- Experienced with building and deploying NLP and voice response applications (including IVR and
- contact center intelligence)
- Familiarity with Google's Vertex AI tech stack
- Experience building applications with modern web component frameworks (such as React & Angular) Staff AI Engineer: Is this role right for you? In this role, you will: Deliver and Scale Agentic AI Solutions:
- Serve as the technical lead and primary engineering point person for AI use cases within the focus
- area, owning technical decomposition, delivery coordination, dependency management, and execution
- quality from concept through production
- Build partnerships with business domains to demonstrate the art of possible and translate business
- requirements to delivery timelines and features.
- Design, build, and productionize LLM-powered and agentic applications, including retrievalaugmented
- generation (RAG), multi-step reasoning workflows, structured outputs, and prompt safety.
- Work hands-on to de-risk complex problems by writing, reviewing, and operating production-grade
- AI systems.

Architect

Secure, Reliable, and Observable Systems:

- Align use case design with platform patterns, governance expectations, and operational support
- models.
- Ensure systems are testable, observable, and resilient, with automated testing and clear operational
- feedback loops.
- Design and operate secure, low-latency services and microservices with modern authentication and
- authorization.
- Contribute to architectural discussions, platform capabilities, and evolving best practices for AI




- development.
- Collaborate with platform, security, and risk partners to ensure systems meet enterprise compliance,
- operational, and governance standards.

Influence Technical

Direction and Engineering Culture - Take ambiguous problems and translate them into clear technical solutions, communicating trade-offs

- and constraints.
- Model a culture of engineering excellence, inclusion, and continuous learning — digging into root
- causes and sharing durable lessons.
- Influence technical direction beyond the immediate team by contributing reusable patterns,
- engineering standards, and architectural guidance across AI initiatives.
- Mentor peers through code reviews and design discussions, raising the bar for quality, ownership, and
- long-term thinking.

Required Qualifications

- Experience leading complex AI initiatives across multiple stakeholders from business case through
- production rollout
- Ability to make sound technical trade-offs across speed, risk, scalability, and maintainability
- Experience in AI safety, evaluation, and responsible AI practices.
- Strong communicator with the ability to manage relationships, align stakeholders, and navigate
- dependencies across projects and products
- Extensive experience in Python and its core data science libraries (e.g., Scikit-learn, Pandas, NumPy,
- Matplotlib/Seaborn).
- Hands-on experience building LLM-powered applications — retrieval, agents, structured outputs,
- prompt safety.
- Strong experience in full stack fundamentals and microservices. Production experience with API
- authentication and authorization (OAuth 2.0, OpenID Connect, and SAML) is required.
- Deep understanding of structured and unstructured data management and their corresponding
- technologies.
- Proven experience in automated testing, including unit and functional testing, and the ability to
- develop test strategies and design automation frameworks.

Preferred Qualifications

- Served as tech lead for an AI driven product and established partnership with product management
- Experience with Agentic AI frameworks and designing multi-step AI reasoning processes
- Experience with MLOps principles and tools for model versioning (e.g., Git), containerization (e.g.,
- Docker), and continuous integration/continuous deployment (CI/CD) of machine learning models
- Solid theoretical and practical knowledge of classical machine learning algorithms (e.g.,
- classification, regression, clustering, dimensionality reduction) and their applications in areas such as
- fraud detection, credit risk scoring, or customer segmentation
- Experienced with building and deploying NLP and voice response applications (including IVR and
- contact center intelligence)
- Familiarity with Google's Vertex AI tech stack
- Experience building applications with modern web component frameworks (such as React & Angular) Disclaimer: AI may be used in evaluating candidates. This posting is for an existing vacancy.

📌 Staff AI Engineer to serve as technical lead for agentic AI and LLM-powered solutions, owning delivery from concept through production while aligning stakeholders, dependencies, and platform standards, for a digital banking client. (Toronto)
🏢 S.i. Systems
📍 Toronto