Data/AI Engineer Job at Modoras Accounting Syd (Toronto)

Job Description

Guidepoint seeks an experienced Data/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 Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s 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 Senior 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 Guidepoint’s products.

Job Responsibility

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

Requirements

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
Proven track record of designing, building, and scaling distributed, production-grade systems
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
Hands-on experience deploying and managing applications on a major cloud platform (Azure preferred, AWS/GCP acceptable) using containerization (Docker) and orchestration (Kubernetes, Helm)
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
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
Familiarity with large-scale data processing platforms and tools (e.g., Databricks, Apache Spark)
Practical experience with libraries and frameworks like LangChain or LlamaIndex for building LLM-powered applications
Demonstrated ability to lead complex technical projects and foster the growth of other engineers

What we offer

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

Modoras Accounting Syd - All Job Offers

Select Country

Data/AI Engineer

Job Description

Job Responsibility

Requirements

What we offer

Looking for more opportunities?

Data/AI Engineer

Associate Data/AI Engineer

Lead Program Security Engineer

Senior Staff AI Engineer

AI Solution Architect (Insurance) - Agentic AI & Azure

Cloud Technical Architect (Presales)

Senior Presales Solutions Architect – Applications & Modernization

Enterprise Account Executive (Financial Services)

Enterprise Account Executive (Healthcare & Life Sciences)

Our AI answers in your language