Palona AI

We are currently seeking a AI Engineer to join our team.

The AI Engineer is responsible for designing, building, and delivering highquality AI technology solutions, including agentic AI applications, retrievalbased 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 decisionmaking across the organization.

Here's what would be included as a part of your typical day

1. AI Technology Design & Development: Design and implement AI technology solutions, including agent behaviors, retrievalaugmented intelligence, and integration of models into applications and workflows. Build secure and reliable components, and integrations to support AIdriven interactions and decisioning. Apply strong software engineering practices, including testing, performance optimization, telemetry, and documentation
2. AI Application Implementation: 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.
3. Data Access & Retrieval Engineering: Implement secure data access strategies across structured and unstructured sources. Build and maintain retrieval pipelines (e.g., search/query components, embeddingbased retrieval, document ingestion pipelines). Ensure data usage aligns with privacy, security, and compliance requirements. 
4. Security, Quality & Compliance: 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 AIenabled solutions. Conduct code reviews, implement automated testing, and validate AI outputs for accuracy and safety.
5. Team Support and Collaboration: 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.
6. Research & Continuous Improvement: 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 knowledgesharing and technical learning activities.

Required Skills, Experience & Qualifications

• Bachelor's degree in computer science, Engineering, or related field.
• 5 years of experience in software engineering, AI engineering, or related technical roles.
• Handson experience building production-grade AI components, agentbased workflows, intelligent automation, or retrievalbased 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 problemsolving 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 crossfunctional coordination.
• Strong attention to detail and focus on quality, security, and longterm 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, retrievalaugmented intelligence).
• Solid understanding of cloud architectures, identity/security fundamentals, and observability.
• Ability to rapidly learn new tools and frameworks in the fastmoving AI ecosystem.
• Displays an understanding of risk and risk ownership by being able to demonstrate adherence to policies and procedures.