AI Engineer

First West•Township of Langley, BC

3d•CA$90,400 - CA$115,800•Hybrid

About The Position

The AI Engineer is responsible for designing, building, and delivering high-quality AI technology solutions, including agentic AI applications, retrieval-based intelligence, automation components, and secure system integrations. This role blends software engineering with modern AI development approaches to create reliable, safe, and scalable capabilities that improve user experience, operational efficiency, and decision-making across the organization.

Requirements

Bachelor’s degree in computer science, Engineering, or related field.
5 years of experience in software engineering, AI engineering, or related technical roles.
Hands-on experience building production-grade AI components, agent-based workflows, intelligent automation, or retrieval-based systems.
Familiarity with enterprise AI platforms and modern cloud architectures (experience with the Microsoft ecosystem is an asset).
Experience working within regulated environments is preferred.
Strong problem-solving skills and the ability to understand complex systems.
Excellent communication and collaboration skills.
Able to work effectively with both technical and business teams.
Ability to balance independent execution with teamwork and cross-functional coordination.
Strong attention to detail and focus on quality, security, and long-term maintainability.
Strong communication and interpersonal skills.
Experience with interpreting and authoring software architecture documents.
High-energy, “can-do” attitude with strong relationship-building skills.
Strong foundation in software engineering, APIs, distributed systems, and secure integrations.
Proficiency with modern AI development practices (agentic workflows, reasoning design, retrieval-augmented intelligence).
Solid understanding of cloud architectures, identity/security fundamentals, and observability.
Ability to rapidly learn new tools and frameworks in the fast-moving AI ecosystem.
Displays an understanding of risk and risk ownership by being able to demonstrate adherence to policies and procedures.

Nice To Haves

Experience with the Microsoft ecosystem is an asset.

Responsibilities

Design and implement AI technology solutions, including agent behaviors, retrieval-augmented intelligence, and integration of models into applications and workflows.
Build secure and reliable components, and integrations to support AI-driven interactions and decisioning.
Apply strong software engineering practices, including testing, performance optimization, telemetry, and documentation.
Translate business requirements into functional AI components, ensuring clarity, feasibility, and alignment to enterprise technical standards.
Develop and refine prompts, reasoning logic, and decisioning flows within agentic applications.
Troubleshoot issues in AI behavior, grounding, retrieval, and integration layers.
Implement secure data access strategies across structured and unstructured sources.
Build and maintain retrieval pipelines (e.g., search/query components, embedding-based retrieval, document ingestion pipelines).
Ensure data usage aligns with privacy, security, and compliance requirements.
Ensure all AI components adhere to identity and access controls, data security requirements, auditability, and content safety guidelines.
Maintain awareness of regulatory expectations (including OSFI and FCAC) as they relate to AI-enabled solutions.
Conduct code reviews, implement automated testing, and validate AI outputs for accuracy and safety.
Work closely with internal IT groups, including Cyber Security, Data, Cloud Infrastructure, Architecture, Software Development, and IT Operations to ensure successful, secure, and scalable operationalization of AI technology solutions.
Partner with business stakeholders, product teams, and subject-matter experts to ensure AI solutions are aligned with desired business outcomes and deliver measurable value.
Stay current with advancements in AI engineering patterns, tooling, and development practices.
Recommend improvements to frameworks, automation, and engineering processes to enhance solution reliability and scalability.
Participate in internal knowledge-sharing and technical learning activities.