Oxford Properties→
Software Engineer (AI) at Oxford Properties in Toronto, Ontario, CA
Skills
Job Description
Choose a workplace that empowers your impact.
Join a global workplace where employees thrive. One that embraces diversity of thought, expertise and experience. A place where you can personalize your employee journey to be — and deliver — your best.
We are a purpose-driven, dynamic and sustainable pension plan. An industry leading global investor with teams in Toronto to London, New York, Singapore, Sydney and other major cities across North America and Europe. We embody the values of our 665,000 members, placing their best interests at the heart of everything we do.
Join us to accelerate your growth & development, prioritize wellness, build connections, and support the communities where we live and work.
Don’t just work anywhere — come build tomorrow together with us.
Know someone at OMERS or Oxford Properties? Great! If you're referred, have them submit your name through Workday first. Then, watch for a unique link in your email to apply.
Why Join Us?
We are looking for a highly motivated early-career Software Engineer to join our Pension Products & Technology team in Toronto. You will work at the intersection of modern software engineering and emerging AI/ML capabilities, helping build next-generation digital solutions for OMERS Pensions.
You will be part of a high-impact team focused on leveraging cloud, distributed systems, and Generative AI to deliver intelligent, scalable, and secure solutions for our members and internal users.
This is an opportunity to learn, grow, and contribute to real-world AI-powered systems while working alongside experienced architects and engineers.
Role & Responsibilities
Design, develop, test, and deploy scalable backend services and applications
Contribute to end-to-end feature development including design, implementation, and deployment
Assist in building and maintaining architectural artifacts such as data flows, APIs, and deployment models
Collaborate with senior engineers and architects to implement scalable and secure system designs
Participate in code reviews and contribute to improving code quality, maintainability, and performance
Work with cloud platforms (Azure or GCP) to deploy and manage applications
Develop and integrate APIs (REST, gRPC)
Support microservices-based and event driven architectures
Contribute to Proof of Concepts (POCs) for new technologies, especially in AI/ML and GenAI space
Work closely with DevOps teams to support CI/CD pipelines and deployments
Create and maintain technical documentation
Collaborate with product owners and business teams to understand requirements and translate them into technical solutions
AI/ML & Generative AI Responsibilities
Understand fundamentals of Machine Learning and Neural Networks
Connect neural network fundamentals (weights, training data distribution, loss optimization) to observable issues like hallucination, bias, and overconfidence in responses
Build a practical understanding of how LLMs generate outputs (token-by-token prediction, temperature, top-p) and tune them based on use case needs (deterministic vs creative tasks)
Work with RAG pipelines and evaluate retrieval quality (relevance of chunks, ranking effectiveness, context injection impact on answers)
Evaluate LLM outputs using practical techniques like A/B testing prompts, golden datasets, and regression testing across model versions
Define use-case specific evaluation criteria (e.g., factual accuracy, completeness, format adherence, reasoning correctness) instead of relying on generic benchmarks
Analyze failures by mapping them to root causes such as context window limits, poor retrieval grounding, token truncation, or attention dilution
Assist in building AI-powered features such as summarization, classification, and insights generation
Design prompts and system instructions informed by how transformers prioritize context (e.g., instruction placement, few-shot positioning)
Support fine-tuning or customization approaches for AI models (where applicable)
Build test cases that intentionally stress model weaknesses (long context, conflicting instructions, ambiguous queries)
Integrate AI services (Azure OpenAI, Gemini, or Claude) into applications
Ensure responsible AI usage, including data privacy and security considerations
Required Skills & Experience
1–2 years of hands-on experience in software development
Strong programming skills in at least one language: Python or Java
Foundational understanding of Neural Networks and Transformers (attention, embeddings, tokenization) and how they impact LLM behavior
Practical knowledge of LLMs/Generative AI, including prompt engineering, hallucinations, context limits, and output variability
Understanding of RAG, embeddings, and vector search, and when to use them vs prompt-only approaches
Awareness of fine-tuning vs prompting vs grounding trade-offs
Ability to analyze and debug LLM outputs and define basic evaluation criteria (accuracy, completeness, format adherence)
Experience with AI/ML libraries or platforms (Langchain, TensorFlow, PyTorch, or similar)
Exposure to AI APIs such as Azure OpenAI or similar platforms
Basic understanding of backend development frameworks (Spring Boot or Fast API etc.)
Familiarity with APIs and web services (REST preferred)
Understanding of SQL and/or NoSQL databases (Postgres, MongoDB, etc.)
Basic knowledge of cloud platforms (Azure or GCP preferred)
Understanding of software development lifecycle and Agile methodologies
Exposure to microservices and distributed systems concepts
Familiarity with containerization (Docker) and basic Kubernetes concepts is a plus
Strong problem-solving and analytical skills
Ability to learn quickly and adapt to new technologies
Engineering & Architecture Foundations
Basic understanding of:
Microservices architecture
Event-driven design
Distributed systems fundamentals
API design principles
Awareness of system scalability, reliability, and performance considerations
Understanding of security and data privacy best practices
Soft Skills
Strong communication and collaboration skills
Ability to work in a team-oriented environment
Eagerness to learn and grow in both software engineering and AI domains
Attention to detail and commitment to quality
Ability to take initiative and contribute ideas
Education
Bachelor’s degree in computer science, Engineering, or equivalent demonstrated experience through projects, internships, or work experience
Nice to Have
Internship or project experience in AI/ML or cloud-based applications
Exposure to CI/CD pipelines and DevOps practices
Knowledge of data processing and analytics workflows
What Success Looks Like
You contribute to production-grade systems within your first few months
You actively participate in building AI-enabled features
You demonstrate growth in both engineering fundamentals and AI/ML capabilities
You collaborate effectively with cross-functional teams
This role is ideal for someone early in their career who wants to build strong foundations in both modern software architecture and AI-driven application development.
This posting is for an existing vacancy.
The expected salary range for this position is $72,000.00 - $108,000.00 per year.
You may also be eligible to receive an annual Incentive Award pursuant to our Short-term Incentive plan and our Long-Term Incentive plan (if applicable), and to participate in our group benefits and retirement plans – details on these elements of compensation are included within OMERS & Oxford offer letters.
As one of Canada’s largest defined benefit pension plans, our people-first culture is at its best when our workforce reflects the communities where we live and work — and the members we proudly serve.
From hire to retire, we are an equal opportunity employer committed to an inclusive, barrier-free recruitment and selection process that extends all the way through your employee experience. This sense of belonging and connection is cultivated up, down and across our global organization thanks to our vast network of Employee Resource Groups with executive leader sponsorship, our Purpose@Work committee and employee recognition programs.
Artificial intelligence (AI) tools are used to support certain stages of the OMERS recruitment process. While AI assists us in our process, human judgment and decision-making remain central to our candidate experience.