Senior AI Engineer

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About the role

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-en

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