AI Engineer

Pure Facts is the leader in the Revenue Performance Management category for wealth and asset management firms. The Pure Revenue 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, Pure Facts has helped leading financial institutions turn revenue from an operational process into a strategic advantage.

At Pure Facts, 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.

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

• Design and build LLM-powered applications and AI agents for both internal and client-facing use cases
• Develop solutions such as:
• AI copilots for internal teams and clients
• Intelligent workflow automation agents
• Natural language interfaces for data and reporting
• Implement prompt engineering, tool usage, and agent orchestration frameworks

• 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 analytics
• Client reporting and communication
• Operational efficiency across workflows

• Integrate LLMs into Pure Facts’ 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

• Design and implement RAG pipelines using structured and unstructured data sources
• Work with:
• Vector databases (e.g., Pinecone, Weaviate)
• Embedding models and semantic search
• Ensure accurate, relevant, and context-aware outputs from AI systems

• Develop frameworks to evaluate LLM outputs for quality, accuracy, and reliability
• Continuously optimize prompts, models, and workflows
• Monitor system performance and implement improvements

• Leverage and integrate tools such as:
• OpenAI, Azure OpenAI, or similar LLM providers
• Lang Chain, Llama Index, or agent frameworks
• APIs, microservices, and cloud infrastructure
• Collaborate with MLOps to ensure scalable and maintainable deployments

• Ensure AI solutions…