Senior AI Engineer

Posted 14 Days Ago
Be an Early Applicant
Toronto, ON, CAN
Hybrid
175K-210K Annually
Senior level
Marketing Tech
The Role
Build and productionize real-time conversational AI systems using voice, chat, LLM orchestration, retrieval, and multi-channel session management. Own services from architecture through Kubernetes/Azure deployment and operations. Develop evaluation infrastructure, tune LLM pipelines for quality, latency, and cost, integrate AI and voice vendors, and establish engineering practices for a growing team. Partner with product and compliance stakeholders to encode domain rules into reliable AI systems.
Summary Generated by Built In

Overview:

Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale — combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets.

You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership.

This role is hybrid in our Toronto Office

What You'll Do:

  • Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure.
  • LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code — not just prompts.
  • Multi-channel session management: stateful user interactions that move seamlessly across channels.
  • Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back.
  • Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes.
  • Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads.
  • Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors.
  • Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them.
  • Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable.
  • Partner with product and compliance stakeholders to encode domain rules into the system.
  • Set engineering patterns for a growing team: code review, observability, incident habits.

What You Have:

  • 6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestration, RAG/grounding, structured outputs, eval-driven iteration.
  • Strong TypeScript or Python; comfortable working across both.
  • Real-time or streaming systems experience: WebSockets, WebRTC, audio pipelines, or comparable low-latency work.
  • Cloud-native production experience: containers, Kubernetes, CI/CD, observability. Azure a plus.
  • Familiarity with agent/LLM frameworks such as LangGraph, LangChain, or CrewAI — hands-on exposure is enough; we care that you know the landscape and when plain code beats a framework.
  • Working familiarity with vector databases and embedding-based retrieval.
  • Pragmatic product judgment: you scope prototypes, kill weak approaches with data, and ship.

Nice-to-have:

  • Voice AI: telephony platforms, conversational agent frameworks, STT/TTS, turn-taking/VAD.
  • Knowledge graphs or large-scale search/retrieval systems.
  • Regulated or compliance-sensitive domains (healthcare, finance).
  • Eval harnesses or LLM-as-judge systems.

What We Offer: 

The annual base salary range for this position is 175,000-210,000 CAD. 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 

About Guidepoint: 

Guidepoint powers end-to-end research workflows for the world’s best research teams.

Backed by a global network of more than 2 million experts and over 1,600 employees, Guidepoint delivers real-time access to expertise, primary research, and actionable knowledge that help organizations make informed decisions. Through consultations, surveys, events, proprietary content, and AI-enabled tools, we support every stage of the decision-making process—from developing hypotheses and gathering insights to validating assumptions and building conviction for critical decisions.

At Guidepoint, our success relies on the diversity of our employees, experts, and clients, which enables us to foster meaningful connections and a broad range of perspectives. We are committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.

#LI-LG1

#LI-HYBRID

This job posting is for an existing vacancy.  The salary offered will be based on the successful candidate’s skills, experience, qualifications, and location.

Compensation
$175,000—$210,000 CAD

Skills Required

  • 6+ years of software engineering experience
  • 2+ years building LLM-powered products in production
  • Experience with LLM orchestration, retrieval-augmented generation or grounding, structured outputs, and evaluation-driven iteration
  • Strong TypeScript or Python skills, with comfort working across both
  • Experience with real-time or streaming systems, such as WebSockets, WebRTC, audio pipelines, or comparable low-latency systems
  • Cloud-native production experience with containers, Kubernetes, CI/CD, and observability
  • Familiarity with LangGraph, LangChain, CrewAI, or comparable agent and LLM frameworks
  • Working familiarity with vector databases and embedding-based retrieval
  • Pragmatic product judgment, including scoping prototypes, evaluating approaches with data, and shipping products
  • Experience with Azure
  • Voice AI experience, including telephony platforms, conversational agent frameworks, STT/TTS, turn-taking, or VAD
  • Experience with knowledge graphs or large-scale search and retrieval systems
  • Experience in regulated or compliance-sensitive domains such as healthcare or finance
  • Experience with evaluation harnesses or LLM-as-judge systems

Guidepoint Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Guidepoint and has not been reviewed or approved by Guidepoint.

  • Leave & Time Off Breadth — Paid time off and sick days are considered competitive for early‑career roles, with separate allocations for PTO and sick time. This breadth supports baseline work-life needs beyond just holidays.
  • Retirement Support — A 401(k) plan with company matching is highlighted and aligned with mid‑market expectations. Employer verification of the match underscores a tangible long‑term benefit.
  • Wellbeing & Lifestyle Benefits — A casual hybrid work environment, wellness activities, team events, commuter support, and office perks are emphasized. These culture‑oriented offerings add non‑cash value to the overall package.

Guidepoint Insights

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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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