AI Engineer PureFacts Financial Solutions Toronto, Ontario, Canada About this position About PureFacts Financial Solutions

PureFacts is the leader in the Revenue Performance Management category for wealth and asset management firms. The PureRevenue Platform helps organizations maximize revenue potential by connecting pricing, billing, compensation, advisor behavior, and AI-powered intelligence within a single Revenue Book of Record. By transforming fragmented revenue processes into a coordinated growth system, firms gain greater visibility, stronger pricing discipline, improved revenue capture, and more effective advisor alignment. The result is faster organic growth, improved profitability, and increased enterprise value. For more than 25 years, PureFacts has helped leading financial institutions turn revenue from an operational process into a strategic advantage.

At PureFacts, we are building an AI-native platform and company. We embed AI, intelligent automation, and agentic workflows across our products and operations to detect anomalies, surface insights, streamline repetitive work, and support faster, better decision-making. In a highly regulated industry, we believe AI must be practical, governed, and auditable—amplifying human expertise while helping our teams and clients focus on higher-value, strategic work.

About PureFacts Financial Solutions

PureFacts is the leader in the Revenue Performance Management category for wealth and asset management firms. The PureRevenue Platform helps organizations maximize revenue potential by connecting pricing, billing, compensation, advisor behavior, and AI-powered intelligence within a single Revenue Book of Record. By transforming fragmented revenue processes into a coordinated growth system, firms gain greater visibility, stronger pricing discipline, improved revenue capture, and more effective advisor alignment. The result is faster organic growth, improved profitability, and increased enterprise value. For more than 25 years, PureFacts has helped leading financial institutions turn revenue from an operational process into a strategic advantage.

At PureFacts, we are building an AI-native platform and company. We embed AI, intelligent automation, and agentic workflows across our products and operations to detect anomalies, surface insights, streamline repetitive work, and support faster, better decision-making. In a highly regulated industry, we believe AI must be practical, governed, and auditable—amplifying human expertise while helping our teams and clients focus on higher-value, strategic work.

About the role The

AI Engineer (LLM/Agent)

will own the conversational layer that describes Purefacts’ ML model outputs to end users, develop a "Revenue Assistant" Agent from R&D; through to prototype, and design context architecture grounded in client-specific pricing data. Builds evaluation and safety frameworks. This role sits at the intersection of

machine learning,



software engineering, and product , focusing on building intelligent systems that can

reason, automate workflows, and augment human decision-making .

You will play a key role in advancing PureFacts’

AI-first strategy , developing AI-powered copilots, agents, and automation tools that reduce manual work, improve productivity, and deliver meaningful client value.

What you'll do LLM & Agent Development

Design and build

LLM-powered applications and AI agents

for both internal and client-facing use casesDevelop solutions such as:AI copilots for internal teams and clientsIntelligent workflow automation agentsNatural language interfaces for data and reportingImplement prompt engineering, tool usage, and agent orchestration frameworks

AI-First Automation & Use Cases Identify opportunities to

replace manual processes with AI-driven automation Build systems that enable users to

interact with complex data through natural language Develop AI solutions that enhance:Revenue insights and analyticsClient reporting and communicationOperational efficiency across workflows

System Design & Integration Integrate LLMs into

PureFacts’ SaaS platform and data systems Build APIs and services to support

AI-powered features Work with data and engineering teams to ensure

secure, scalable, and reliable integrations

Retrieval-Augmented Generation (RAG) & Data Integration Design and implement

RAG pipelines

using structured and unstructured data sourcesWork with:Vector databases (e.g., Pinecone, Weaviate)Embedding models and semantic searchEnsure accurate, relevant, and context-aware outputs from AI systems

Evaluation, Testing & Optimization Develop frameworks to

evaluate LLM outputs for quality, accuracy, and reliability Continuously optimize prompts, models, and workflowsMonitor system performance and implement improvements

AI Infrastructure & Tooling Leverage and integrate tools such as:OpenAI, Azure OpenAI, or similar LLM providersLangChain, LlamaIndex, or agent frameworksAPIs, microservices, and cloud infrastructureCollaborate with MLOps to ensure

scalable and maintainable deployments

Responsible AI & Governance Ensure AI solutions are

secure, compliant, and aligned with responsible AI principles Address:Data privacy and securityModel hallucination and reliabilityExplainability and transparency

Cross-Functional Collaboration Partner with Product, Engineering, and Client teams to translate

AI capabilities into business value Help stakeholders identify opportunities to





increase efficiency and reduce manual effort Communicate technical concepts in a transparent, practical way

Qualifications 2+ years building production, customer-facing LLM/GenAI applications, including vector databases, RAG pipelines , agent orchestration6-8+ years of total back-end software engineering experienceDeep, hands-on experience building with agent frameworks (e.g., Microsoft Agent Framework, Google ADK, LangGraph, etc.), including designing custom orchestration patterns beyond out-of-the-box templatesDemonstrated ownership of evaluation frameworks and pipelines and design of deterministic guardrails/safety controls in regulated or compliance-sensitive contextsExperience in SaaS, fintech, or other data-driven, regulated environments strongly preferred

Technical Skills Expert-level Python (required)Deep experience with:LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.), including cost/latency tradeoffs at scaleAgent development frameworks (LangChain, LlamaIndex, LangGraph, or similar)API and microservices architecture, including integrating LLM and ML model components into larger systemsData processing (SQL, Python data libraries) and pipeline design for both retrieval-quality data and model training dataSolid working knowledge of:Vector databases and embedding strategies (selection, tuning, hybrid search)Cloud platforms (AWS, Azure), including deployment and scaling of AI/ML workloads

AI, Agent & ML Model Expertise Proven experience architecting and shipping:Retrieval-Augmented Generation (RAG) systems at production scaleMulti-step agent workflows with error handling and recoveryTool-using agents and end-to-end automation systemsStrong, applied understanding of:LLM limitations, failure modes, and optimization techniques (prompt design, fine-tuning vs. RAG tradeoffs, latency/cost optimization)Evaluation methods for generative AI (offline eval sets, human-in-the-loop review, regression testing for prompt/model changes, model performance monitoring)Safety and guardrail design appropriate to regulated environments (PII handling, hallucination mitigation, model bias/fairness checks, audit trails)

Operations & Reliability Experience operating AI/ML systems in production, including uptime, latency, and cost monitoring for both LLM and model-serving infrastructureFamiliarity with incident response and root-cause analysis for model or agent failures (degraded outputs, drift, hallucination spikes, pipeline breakages)Ability to define and track model/agent health metrics (accuracy, drift, confidence calibration, usage patterns) and act on them proactively

Automation & Product Mindset Genuine passion for using AI/ML to automate workflows and eliminate low-value workAbility to independently translate ambiguous AI/ML capabilities into practical, high-impact products with minimal guidanceStrong bias toward user experience, reliability, and real-world adoption over technical novelty

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📌 AI Engineer (Winnipeg)
🏢 PureFacts Financial Solutions
📍 Winnipeg