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Lead Software Engineer, AI & Emerging Tech

Urban Ridge Supplies

Purpose. Performance. People.

Joining CPP Investments means joining one of the world’s most admired and respected institutional investors to drive a single mandate: to deliver strong, sustainable returns for generations of Canadians.

With a long-term horizon and global reach, we deploy capital at scale across public and private markets. Our size, stability, and disciplined investment philosophy allow us to pursue complex opportunities and build enduring partnerships worldwide.

For our people, this means meaningful work with tangible impact, real opportunity, and collaboration with exceptional colleagues who value partnership and performance. Here, you’ll contribute to outcomes that matter alongside team members committed to excellence and shared success.

The Role

As a Lead Engineer for AI & Emerging Tech, you will drive AI platform enablement across the enterprise, you will drive the design, development, and deployment of next-generation tech and AI-powered solutions that unlock business value across the organization. This is a hands-on, leadership role, where you will code, architect, pilot and build robust solutions, mentor engineers, and push the boundaries of what’s possible with AI, AWS cloud, and emerging technologies.

You’ll partner with cross-functional teams like Information Security, Engineering, Risk, Legal and Compliance teams to define and agree on AI platform controls, implement those controls through configuration and code changes that make AI capabilities usable in a controlled enterprise environment. The ideal candidate is a senior engineer passionate about coding, platform enablement with deep expertise in python, emerging tech, cloud infrastructure, and AI/ML —and thrives in a fast-paced, exploratory environment.

The Team

As a Lead Software Engineer, you will guide and participate in building, enabling and supporting value-add technology solutions, AI tools and products.  You will also demonstrate leadership and drive engineering excellence within your team and influence the same across the Technology & Data department.

Accountabilities

  • Lead and actively contribute to enable upcoming AI features and products for the organization, onboarding users/teams and use cases onto enterprise AI platforms (e.g. OpenAI, Gemini, Anthropic, Amazon Bedrock, LLM gateways, and agentic frameworks).
  • Coordinate with cross-functional stakeholders — Information Security, Risk, Compliance, Legal, and business teams — to review, negotiate, and agree on platform controls and guardrails for implementation.
  • Design, build, and maintain scalable Gen AI platform capabilities, including LLM pipelines, agentic workflows, MCP integrations, and Graph/RAG architectures, using clean, maintainable Python and AWS-native tooling.
  • Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.
  • Optimize performance of AI products, Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains.
  • Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization's AI roadmap.
  • Own end-to-end delivery of platform enablement initiatives; manage timelines, deliverables, and milestones using Agile practices (Scrum/Kanban).
  • Advice, maintain, monitor and support AI platform and product users.

What You Bring

  • Bachelor’s degree in computer science, engineering, or a related field; advanced degrees or certifications are an asset.
  • 6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives.
  • Experience in:
  • Gen AI platforms, models (ChatGPT/Codex, Claude, Gemini, Copilot) and prompt engineering techniques
  • Hands-on experience implementing controls through configuration and code: IAM/access policies, guardrails, logging and audit trails, quota/rate limiting, and network/data-protection controls.
  • Agentic AI, MCP, and Graph/RAG architectures
  • Gen AI Framework (Amazon Bedrock, LangChain, LlamaIndex, Hugging Face, PandsAI)
  • Web application development using Next.js, React, TypeScript/JavaScript
  • AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation)
  • Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments
  • ETL orchestration using Apache Airflow/DAGs
  • Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization
  • Python programming (NumPy, Pandas, Matplotlib, Boto3)
  • Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium,)
  • Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).
  • Knowledge of LLM fine tuning techniques
  • Experience in BI tools like QuickSight, Tableau, and knowledge of financial markets and enterprise data systems

You are motivated to contribute to something larger than yourself, approach complex challenges with rigor, and hold yourself to high standards in a collaborative, performance-driven environment.

We provide colleagues with cutting-edge AI tools, dedicated learning time, and practical support to help them deliver with greater impact.

Inclusion & Accessibility

CPP Investments is committed to equitable access to employment and building a workforce that reflects diverse talent and perspectives. If you require accommodation at any stage of the recruitment process, please let us know and we will work with you to meet your needs.

Attention: Protect Yourself from Fraud

CPP Investments is committed to a secure and transparent recruitment process. We will never ask candidates for payment or financial information at any stage of hiring. All legitimate opportunities are posted on our careers page, and communications will come from our applicant tracking system, Workday.

CPP Investments may use AI tools to help screen and assess applicants by analyzing resumes and applications for relevant skills and experience. These tools support, but do not replace, human decision-making.


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