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 up-to-date 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

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)

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 delive (Toronto)
🏢 S.i. Systems
📍 Toronto