AI Engineer

Overview:

Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoints vision for the future aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoints Next-Gen research enablement platform and data products.

This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems including large language model (LLM) applications and research agents while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoints products.

Guidepoints Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals businesses and the world smarter through personalized knowledge-sharing solutions the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.

This is a hybrid position based in Toronto.

What Youll Do:

• Architect and Build Production Systems: Design build and operate scalable low-latency backend services and APIs that serve Generative AI features from retrieval-augmented generation (RAG) pipelines to complex agentic systems.
• Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications including system design development deployment (CI/CD) monitoring and optimization in production environments like Databricks and Azure Kubernetes Service (AKS).
• Optimize RAG Pipelines: Continuously improve retrieval and generation quality through techniques like retrieval optimization (tuning k-values chunk sizes) using re-rankers advanced chunking strategies and prompt engineering for hallucination reduction.
• Integrate Intelligent Systems: Engineer solutions that seamlessly combine LLMs with our proprietary knowledge repositories external APIs and real-time data streams to create powerful copilots and research assistants.
• Champion LLMOps and Engineering Best Practices: Collaborate with data science and engineering teams to establish and implement best practices for LLMOps including automated evaluation using frameworks like LLM Judges or MLflow AI observability and system monitoring.
• Evaluate and Implement AI Strategies: Systematically evaluate and apply advanced prompt engineering methods (e.g. Chain-of-Thought ReAct) and other model interaction techniques to optimize the performance and safety of proprietary and open-source LLMs.
• Mentor and Lead: Provide technical leadership to junior engineers through rigorous code reviews mentorship and design discussions helping to elevate the teams engineering standards.
• Influence the Roadmap: Partner closely with product and business stakeholders to translate user needs into technical requirements define priorities and shape the future of our AI product offerings.

What You Have:

• Experience: A Bachelors degree in Computer Science Engineering or a related technical field with 6 years of professional experience; or a Masters degree with 4 years of professional experience in backend software engineering and Generative AI. This must include a proven track record of designing building and scaling distributed production-grade systems.
• Strong Software Engineering Fundamentals: Deep expertise in Python a major backend framework (e.g. FastAPI Flask) and asynchronous programming (e.g. asyncio). Proficiency in designing RESTful APIs microservices and the complete operational lifecycle including comprehensive testing CI/CD (e.g. ArgoCD) observability monitoring alerting maintaining high uptime and executing zero-downtime deployments.
• Cloud & Infrastructure Proficiency: Hands-on experience deploying and managing applications on a major cloud platform (Azure preferred AWS/GCP acceptable) using containerization (Docker) and orchestration (Kubernetes Helm).
• Production AI Application Experience: 2 years of experience building applications that leverage large language models from providers like OpenAI Anthropic or Google Gemini. Direct experience with modern LLM patterns such as retrieval-augmented generation (RAG) hybrid search using vector databases (e.g. Pinecone Elasticsearch) multi-agent AI systems with tool calls and prompt engineering is required.
• AI System Design and Evaluation: Experience designing and implementing robust evaluation frameworks for LLM-based systems including rubric-based scoring LLM Judges or using tools like MLflow alongside monitoring for performance and drift.
• Large-Scale Data Processing: Familiarity with large-scale data processing platforms and tools (e.g. Databricks Apache Spark).
• Familiarity with the Modern AI Stack: Practical experience with libraries and frameworks like LangChain or LlamaIndex for building LLM-powered applications.
• Leadership and Mentorship: Demonstrated ability to lead complex technical projects and foster the growth of other engineers.

What We Offer:

The annual base salary range for this position is $135000 - $210000. Additionally this position is eligible for an annual discretionary bonus based on performance.

You will also be eligible for the following benefits:

• Paid Time Off
• Comprehensive benefits plan
• Company RRSP Match
• Development opportunities through the LinkedIn Learning platform

Guidepoints Interview Process:

We respect your time and aim to keep the process transparent and efficient. Our Talent Acquisition team members act as advisors throughout the process and help ensure everything runs smoothly so you have a seamless candidate experience. Our goal is to make sure this is a mutual fit for both you and our teams.

1. Talent Acquisition Screen (Virtual 30 minutes)
2. Hiring Manager Interview (Virtual 1 hour)
3. Live Coding & System Design Test (On-site 2 hours)
4. Technical Leadership Interview (Virtual 1 hour)
5. Reference Checks (3 professional references)
6. Offer

About Guidepoint:

Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients decision-making process. Powered by innovative technology real-time data and hard-to-source expertise we help our clients to turn answers into action.

Backed by a network of nearly 1.75 million experts and Guidepoints 1600 employees worldwide we inform leading organizations research by delivering on-demand intelligence and research on request. With Guidepoint companies and investors can better navigate the abundance of information available today making it both more useful and more powerful.

At Guidepoint our success relies on the diversity of our employees advisors and client base which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community regardless of background identity or experience.

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This job post is for a live vacancy. Base salary may vary depending on job-related knowledge skills and experience as well as geographic location.

Compensation

$135000 - $210000 CAD

Required Experience:

IC

Employment Type : Full Time
Experience: years
Vacancy: 1
Monthly Salary Salary: 135000 - 210000