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About the Role

Guidepoint is seeking a Senior AI Engineer to transition AI prototypes into production, shaping the architecture of AI systems that enhance research capabilities. This role involves broad ownership of agent design, evaluation, APIs, and cloud deployment, collaborating with product, engineering, and compliance teams.

Responsibilities

Design and ship multi-agent systems where specialized agents collaborate to complete research tasks.
Enforce permissions, domain rules, workflow boundaries, and output requirements in application code.
Design for safe tool use, clear failure handling, and human review.
Build reliable multi-turn workflows with explicit state management, memory and context strategies, timeouts, retries, and recovery from partial failures.
Build and maintain Python services and APIs that connect agents to Guidepoint products, internal data, and third-party providers.
Build retrieval and search pipelines over large internal knowledge assets.
Return structured, traceable results and indicate supporting sources.
Define and maintain evaluations for task success, factual accuracy, groundedness, completeness, policy adherence, latency, and cost.
Use representative test sets, regression checks, and production feedback to guide improvements and rollout decisions.
Own services from design through production deployment and operations.
Select models and tools, engineer context, define structured outputs, and manage tradeoffs among quality, latency, reliability, and cost.
Put model, retrieval, and voice providers behind clear interfaces.
Establish patterns for code review, testing, observability, incident response, and production readiness.

Requirements

8+ years of software engineering experience, including 3+ years building and operating production AI or LLM-powered products.
A 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.
Demonstrated experience designing and shipping multi-agent or agentic workflows in production, including orchestration, tool use, state management, and failure handling.
Strong Python skills and experience building production APIs and backend services.
Hands-on experience with cloud-native deployment, including containers, Kubernetes, CI/CD, and production observability.
Experience working with Azure and/or Databricks in production environments.
Practical experience with LLM evaluation: creating test sets, measuring quality and accuracy, analyzing failures, and using results to improve systems or gate releases.
Experience with retrieval-augmented generation, embeddings, vector databases, or large-scale search systems.
Understanding of model and workflow risks, including unsupported answers, prompt injection, unsafe tool calls, and data access boundaries—and experience addressing them through system design and code.
Experience operating services with production requirements for reliability, latency, and cost.
Product judgment: ability to scope a useful first version, compare approaches with evidence, and ship iteratively.

Skills

Python
TypeScript
Cloud-native deployment
Containers
Kubernetes
CI/CD
Production observability
Azure
Databricks
LLM evaluation
Retrieval-augmented generation
Embeddings
Vector databases
Large-scale search systems
Agent and orchestration frameworks (e.g., LangGraph, LangChain)
Real-time or streaming systems
WebSockets
WebRTC
Audio pipelines
Low-latency services
Voice AI
Telephony platforms
Speech-to-text
Text-to-speech
Turn-taking
Voice-agent frameworks
Knowledge graphs
Information retrieval
LLM-as-judge methods
Human review workflows
Production monitoring for AI quality

Location

Toronto

Work Type

Hybrid

Experience Level

Senior
8+ years of software engineering experience
3+ years building and operating production AI or LLM-powered products
6+ years of professional experience (with Bachelor's)
4+ years of professional experience (with Master's)

Education Level

Bachelor's degree in Computer Science, Engineering, or a related technical field
Master's degree

Salary/Compensations

$175,000—$210,000 CAD

Benefits

Annual discretionary bonus based on performance
Paid Time Off
Comprehensive benefits plan
Company RRSP Match
Development opportunities through the LinkedIn Learning platform

About the Company

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.
Guidepoint's success relies on the diversity of its employees, experts, and clients, fostering meaningful connections and a broad range of perspectives.
Committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.

Equal Opportunity

Guidepoint is committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.