Senior AI Engineer

Reposted 9 Days Ago
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Toronto, ON
In-Office
Senior level
Marketing Tech
The Role
The Senior AI Engineer will design, build, and operate Generative AI systems and backend platforms, owning the full lifecycle of applications and ensuring quality controls while collaborating with stakeholders on the AI roadmap.
Summary Generated by Built In

Overview:
 
Guidepoint is seeking an experienced Senior AI Engineer 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. 

This role is ideal for an engineer who enjoys owning systems end to end—designing, building, deploying, and operating production-grade AI agents and the backend platforms that support them. 

This is a hybrid position based out of Toronto.

What You’ll Do:   

  • Design, build, and operate scalable, low-latency backend services and REST APIs that power Generative AI capabilities, including retrieval-augmented generation (RAG) pipelines, vector search, and enterprise-grade agentic systems.  
  • Own the full lifecycle of AI applications and agents, from system architecture and development to CI/CD, deployment, agent evaluation, monitoring, and ongoing optimization in production.  
  • Build production-grade research agents and enterprise AI workflows that integrate LLMs with proprietary knowledge, vector databases (e.g., Elasticsearch), internal tools, external APIs, and real-time data.  
  • Design and operate multi-agent AI systems, including tool-calling agents and agent orchestration patterns, to support complex research and enterprise workflows.  
  • Apply AIOps best practices for building, evaluating, deploying, and operating AI agents with strong observability, reliability, and quality controls.  
  • Continuously improve retrieval and generation quality using prompt engineering, retrieval tuning, re-ranking, advanced chunking strategies, and hallucination reduction techniques.  
  • Provide technical leadership through design discussions, code reviews, and mentorship, and partner closely with product and business stakeholders to influence the AI roadmap. 

What You’ll Have:  

  • 6+ years of professional experience (or 5+ with a Master’s degree) designing, building, and scaling distributed, production-grade backend systems, including 2+ years building and operating Generative AI and agentic systems in production.  
  • Strong software engineering fundamentals in Python, including building and scaling REST APIs using frameworks such as FastAPI, with experience in asynchronous programming and microservices.  
  • Hands-on experience building enterprise AI agents and workflows using LLM platforms such as OpenAI, Anthropic (Claude), or Google Gemini, and frameworks like LangChain or agent SDKs.  
  • Experience building and operating within the enterprise AI ecosystem, including custom GPTs or agents, agent builders, connectors/apps, and application or agent SDKs (e.g., OpenAI Apps SDK, ChatKit, or equivalents). 
  • Experience designing and operating agent integration layers (e.g., MCP servers or similar) that connect AI agents to internal APIs, tools, and services, with secure authentication and authorization using enterprise identity platforms such as Okta, Microsoft Entra ID, or OAuth-based systems. 
  • Strong understanding of AI governance, compliance, and responsible AI practices, including access control, auditability, data handling, and secure deployment of AI systems in enterprise environments. 
  • Direct experience with RAG, vector search using databases such as Elasticsearch, multi-agent AI systems, tool-calling agents, prompt engineering, and agent evaluation in production environments.  
  • Cloud-native experience deploying and operating containerized applications on Azure (preferred) or AWS/GCP using Docker and Kubernetes.  
  • Proven ability to lead complex technical initiatives, make sound architectural decisions, and mentor engineers building production-ready AI systems. 

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. 

Top Skills

Anthropic
AWS
Azure
Docker
Elasticsearch
Fastapi
GCP
Google Gemini
Kubernetes
Langchain
Llm Platforms
Openai
Python
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The Company
HQ: New York, NY
2,882 Employees
Year Founded: 2003

What We Do

Guidepoint connects clients with vetted subject matter experts—Advisors—from our global professional network. Our clients leverage the insights and perspectives shared by our Advisors to stay informed and make better business decisions.

Our multinational client list includes nine of the top 10 global consulting firms, hundreds of hedge funds (including five of the largest firms), and many of the largest private equity firms and Fortune-ranked companies. Guidepoint’s fourteen offices on three continents provide 24/7, quick and agile service.

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