Senior AI Engineer

Job Title:

Senior AI Engineer

Job

Location:

Halifax, Nova Scotia – Hybrid

Overview:
Our client provides specialist financial services to alternative investment funds, investors, multinationals and private clients worldwide. With over 10,000 employees in 45 countries, they innovative solutions to meet clients’ evolving needs and deliver exceptional service. As a core member of our technology team, you will work with dedicated professionals to design, build and support secure, cloud-native, AI-enabled applications for the financial services industry.

Using modern software engineering practices, AI-assisted development, and cross-functional collaboration, you will lead the design and delivery of complex AI powered solutions that ensure clients maintain seamless access to their critical information assets while keeping ahead of industry innovation. Within the AI Engineering team, you will lead the design and delivery of document intelligence solutions that classify financial and client documents, extract structured information, and automate complex business processes.

You will work directly with business stakeholders, architects and engineering teams to design scalable AI-powered solutions leveraging large language models, natural language processing, machine learning, document understanding and agentic workflows. In this senior role, you will be expected to influence solution architecture, establish implementation patterns, mentor engineers, and drive the successful delivery of AI initiatives from concept through production.

Quality Model and Ownership

This role aligns with the Developer profile within CDI Quality Model. Quality is built in, not tested in.

• The Platform Team defines requirements, acceptance criteria, service expectations and business risk.
• Quality Engineers define the verification strategy, quality gates, test harnesses and observability.
• AI agents accelerate implementation and testing within approved guardrails.
• The AI Engineer remains accountable for technical correctness, human review of AI-generated output, meaningful tests, secure implementation and production readiness. AI-generated work never self-approves.

You will work as part of a cross-functional agile team to design, build and support secure, cloud-native and AI-enabled applications. In this senior role, you will lead the technical design and delivery of complex AI and machine-learning capabilities across services, making architecture-level decisions within your area of responsibility.

You will also mentor engineers, establish implementation patterns and ensure AI-assisted delivery remains secure, observable, testable and aligned with business intent.

• Participate in and contribute to all agile team activities.
• Own technical specifications, solution design and implementation for complex or high-risk AI and machine-learning capabilities.
• Design scalable AI architectures, including foundation-model integration, retrieval, document processing, agent workflows, model-serving patterns, evaluation, data controls, fallback strategies and human review.
• Key team member in the design and implementation of intelligent document processing solutions, including document classification, information extraction, semantic search, business workflow automation and document understanding capabilities.
• Evaluate candidate algorithms, models, prompts, retrieval approaches and frameworks against business needs, accuracy, operational risk and production constraints.
• Define and implement model adaptation strategies including prompt optimization, retrieval tuning, supervised fine-tuning and evaluation frameworks to improve solution performance.
• Lead the design of data preparation, validation, evaluation and deployment processes supporting AI-enabled solutions.
• Identify data-distribution changes, model degradation, retrieval failures and other conditions that could negatively affect production performance.
• Analyze model and application errors, determine underlying causes and design improvement strategies.
• Set coding, testing, review, MLOps and operational patterns across Python, ReactJS, AWS, AI frameworks and CI/CD workflows.
• Lead reviews of complex AI-generated code and tests, challenge weak assumptions and ensure independent validation against acceptance criteria.
• Define evaluation strategies for accuracy, grounding, safety, latency, reliability, security, cost, bias and model or data drift.
• Design and evolve AI evaluation harnesses, regression datasets, automated…