Guidepoint Logo

Guidepoint

AI Engineer

Posted Yesterday
Be an Early Applicant
Easy Apply
In-Office
Toronto, ON
Mid level
Easy Apply
In-Office
Toronto, ON
Mid level
The AI Engineer II will design and operate AI systems for compliance and editorial workflows, focusing on generative AI, REST APIs, and scalable data pipelines while improving reliability and performance.
The summary above was generated by AI

Overview:

Guidepoint is seeking an AI Engineer II to join our Toronto-based AI team. The Toronto Technology Hub is home to our AI/ML and Data organization, focused on building a modern, responsible AI platform that powers Guidepoint’s research enablement products and enterprise intelligence.  

In this role, you will build and operate AI systems and agents that support compliance, editorial workflows, and intelligent automation. You will work hands-on with Generative AI agents, production-grade APIs, and scalable data pipelines, contributing to their reliability, quality, and long-term operation in production. 

This is a hybrid position based out of Toronto.

 What You’ll Do:

  • Design and implement AI systems and agents that automate compliance and editorial workflows in support of research enablement. 
  • Design and implement agent workflows using frameworks such as LangGraph and LangChain. 
  • Build agents that perform intent interpretation, task decomposition, tool use, web search, and human-in-the-loop escalation. 
  • Build and operate production-grade REST APIs to serve AI and agent capabilities. 
  • Develop and maintain scalable data pipelines and background workers that support AI workloads and agent execution. 
  • Design and maintain retrieval-augmented generation (RAG) pipelines using embeddings, Elasticsearch, structured data, and web-based sources. 
  • Develop and maintain automated evaluation pipelines for agent behavior and outputs using MLflow and related tooling. 
  • Improve agent reliability, latency, and cost through prompt engineering, prompt management techniques, and workflow optimization. 
  • Integrate agents with internal services, APIs, data stores, and asynchronous workers using queues such as RabbitMQ or Redis. 
  • Monitor and operate agent systems using observability platforms such as Datadog, including alerting and incident response. 
  • Debug and mitigate agent failure modes such as hallucinations, tool misuse, and state or orchestration errors. 
  • Manage the full lifecycle of agent systems and supporting APIs, from implementation through deployment and long-term operation using CI/CD pipelines and Kubernetes. 

What You Have: 

  • 3–5 years of professional experience designing, building, and operating production-grade backend systems, including 2+ years of hands-on experience building and operating Generative AI and agent systems in production. 
  • Strong Python engineering skills, with experience building scalable REST APIs using frameworks such as FastAPI, and working knowledge of JavaScript and Node.js. 
  • Hands-on experience building and maintaining agent-based AI systems in production using frameworks such as LangChain or LangGraph. 
  • Experience working with large language models from providers such as OpenAI, Anthropic, or Google Gemini, including prompt engineering and tool integration. 
  • Practical experience building and operating RAG systems using embeddings and retrieval systems such as Elasticsearch. 
  • Experience evaluating AI or agent systems beyond manual testing, including automated or programmatic evaluation using tools such as MLflow. 
  • Familiarity with asynchronous processing and workers using technologies such as RabbitMQ or Redis. 
  • Experience with monitoring, alerting, deployment, and CI/CD pipelines in cloud-native environments using Kubernetes. 
  • Comfortable owning systems independently, including debugging, on-call support, and iterative improvement in production. 

What We Offer:  

  • Paid Time Off 
  • Comprehensive benefits plan 
  • 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.

Backed by a network of nearly 1.75 million experts and Guidepoint’s 1,600 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. 

#LI-EB1

#LI-Hybrid


Top Skills

Anthropic
Ci/Cd
Elasticsearch
Fastapi
Google Gemini
JavaScript
Kubernetes
Langchain
Langgraph
Mlflow
Node.js
Openai
Python
RabbitMQ
Redis

Similar Jobs

Yesterday
Easy Apply
Hybrid
Toronto, ON, CAN
Easy Apply
Mid level
Mid level
Marketing Tech • Mobile • Software
The AI Platform Engineer II will build and maintain services for the AI platform focusing on ML decision-making, implement cloud solutions, troubleshoot incidents, and enhance workflows through collaboration and tools.
Top Skills: AirflowAWSBigQueryCeleryDatadogDataprocFastapiGithub ActionsGoogle Cloud PlatformHelmIbisJenkinsKubernetesMlflowPythonRabbitMQSentrySparkSQLStreamlitTerraform
11 Hours Ago
In-Office
2 Locations
Senior level
Senior level
Insurance • Financial Services
The role involves building scalable AI solutions, enhancing productivity through agentic automations, and integrating LLMs and other advanced AI frameworks.
Top Skills: AdkAgentflowAnthropicAWSAws BedrockCi/CdCrewaiDockerGCPGeminiJavaKubernetesLangchainLanggraphMilvusOpenaiPgvectorPineconePythonTypescriptVertex AiWeaviate
Yesterday
In-Office or Remote
27 Locations
Senior level
Senior level
Healthtech • HR Tech • Insurance • Consulting
Design, build, and deploy production-grade AI systems for healthcare analytics. Collaborate across teams to implement ML models and MLOps pipelines.
Top Skills: Azure Data LakeAzure DatabricksAzure DevopsAzure MlAzure OpenaiDelta LakeDockerGitHuggingfaceJupyterKubernetesLangchainMlflowOpenai ApiOptunaPostgresPower BIPysparkPythonPyTorchScikit-LearnSQLTensorFlowVs CodeXgboost

What you need to know about the Montreal Tech Scene

With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.

Key Facts About Montreal Tech

  • Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
  • Major Tech Employers: SAP, Google, Microsoft, Cisco
  • Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
  • Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
  • Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
  • Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account