Senior AI Engineer

Guidepoint; Toronto; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

A leading research platform is seeking a Senior AI Engineer in Toronto. This role involves architecting AI applications, optimizing RAG pipelines, and mentoring junior engineers. Candidates should have a strong background in Python, cloud infrastructure, and Generative AI systems. This is a hybrid position offering benefits like paid time off and development opportunities.

Benefits

Paid Time Off

Company RRSP Match

Development opportunities through LinkedIn Learning

Qualifications

• 6+ years of professional experience or 4+ years with a Master's degree.
• Experience in backend software engineering and Generative AI.
• Demonstrated ability to lead technical projects.

Responsibilities

• Design and operate scalable backend services for Generative AI.
• Own the lifecycle of AI applications including deployment.
• Integrate LLMs with data streams and APIs.

Skills

Python

Backend frameworks (FastAPI, Flask)

Asynchronous programming (asyncio)

Generative AI

Cloud platforms (Azure, AWS)

Containerization (Docker)

Orchestration (Kubernetes)

Large-scale data processing

LLM applications (OpenAI, Anthropic)

Education

Bachelor’s degree in Computer Science or Engineering

Master’s degree in relevant field

Tools

Databricks

Apache Spark

LangChain

LlamaIndex

Job description

Guidepoint seeks an experienced Senior 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 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.

Guidepoint’s 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 You'll 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 team's 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'll Bring

• Experience: A Bachelor’s degree in Computer Science, Engineering, or a related technical field with 6+ years of professional experience; or a Master’s degree with 4+ years of professional experience in backend software engineering and Generative AI.
• Strong Software Engineering Fundamentals: Deep expertise in Python, a major backend framework (e.g., FastAPI, Flask), and asynchronous programming (e.g., asyncio).
• 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.
• 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.
• 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.

Benefits

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

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.