Lead Software Engineer, AI & Emerging Tech

CPP Investments | Investissements RPC•Toronto, ON

12d•Onsite

About The Position

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.

Requirements

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

Responsibilities

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.