Junior AI Engineer

Job Title:

Junior AI Engineer
Job

Location:

Halifax, Nova Scotia

Overview:
Our client is a global leader in fund services, corporate governance and related asset services with staff across 80 offices worldwide. As a core member of our technology team, you will work with dedicated professionals to 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 help deliver reliable, high-quality 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 assist with developing document intelligence solutions that classify financial and client documents, extract structured data, and drive business process automation. Working closely with business stakeholders, you will contribute to the development, testing and enhancement of AI-powered solutions under the guidance of senior engineers leveraging large language models, natural language processing, document processing services, machine learning, and agentic workflows to solve complex business challenges and create measurable value.

Whatyou will be doing:

You will work in a cross-functional agile team to build and support cloud-native and AI-enabled applications. With guidance from experienced engineers, you will deliver well-defined features, strengthen your software engineering skills and use AI development tools responsibly.

Participate in sprint planning, daily scrums,reviews and retrospectives.

Implement well-defined application features, APIs, data-processing components,prompt sand AI integrations under guidance.

Implement solutions based on established architecture, design patterns and technical specifications.

Support the development of document-processing, machine-learning,RAGand generative AI capabilities.

Write clean,typedand maintainable Python code, and contribute to ReactJS components where required.

Work with common Python data and AI libraries such as Pandas, Num Py and scikit-learn under guidance.

Create andvalidateunit and integration tests for changed behavior, including appropriate errorand edge cases.

Review AI-generated code,testsand documentation before including them in a change.

Troubleshoot defects, address reviewfeedbackand keep technical documentation current.

Support AWS deployments and CI/CD activities using established patterns,controls and runbooks.

Collaborate with Platform, Quality Engineering, data,security and operations colleagues.

Learn and apply software engineering best practices.

Participate in code reviews and incorporate feedback.

Develop proficiency in AI, cloud and software engineering technologies through practical project work.

Contribute to reusable components and documentation.

AI-Native Engineering Expectations

Use AI coding assistants to accelerate learning, implementation, testing and documentation within team guardrails.

Validate generated output for correctness, security, relevance and maintainability.

Career Development Expectations

Demonstrate continuous growth in software engineering, cloud and AI technologies.

Progressively take ownership of increasingly complex features with guidance.

Develop the skills required to independently deliver AI-enabled solutions.

Be able to explain why submitted code and tests exist and what behavior they protect.

Apply established prompt, RAG and AI application test cases, datasets and harnesses with guidance.

Escalate uncertain, sensitive or high-risk outputs for human review.

Demonstrate responsible use of AI coding assistants and development tools.

Seek guidance when generated outputs impact security, compliance, architectural decisions or business‑critical functionality.

Continuously improve understanding of AI development patterns and quality practices.

What you must have:

You must have a Bachelor’s degree in Computer Science, Engineering, Data Scienceor equivalent practical experience.

Up to 2 years of software engineering, data, machine-learningor relevant project experience.

Working knowledge of Python, Git, APIs, automatedtestingand core software engineering practices.

Familiarity with Python libraries such as Pandas, Num Py or scikit-learn.

Foundational understanding of generative AI and machine learning concepts, including prompts, embeddings, retrieval augmented generation (RAG), model evaluation and document processing.

Exposure tonatural-language…