Role Description We are seeking a highly motivated and technically skilled Automation and AI Specialist (AI Lab Lead) to join our Professional Services team. This role is critical to advancing our implementation capabilities by designing and developing innovative automation and AI-driven solutions that accelerate and streamline the configuration of our Mortgage Cadence Platform (MCP). The ideal candidate is passionate about leveraging cutting-edge technologies like Large Language Models (LLMs) and workflow automation platforms (e.g., n8n, Power Automate) to reduce manual effort, improve accuracy, and scale implementation efforts across clients. This individual will collaborate closely with implementation consultants, project managers, configuration specialists, and product teams to identify opportunities and deliver tangible outcomes through automation. - Design, develop, and maintain AI- and automation-driven solutions that support the rapid configuration of MCP for client implementations. - Leverage LLMs (e.g., OpenAI, Claude) to interpret client documentation (e.g., underwriting guidelines, product matrices, policies) and generate configuration outputs. - Build and optimize automated workflows using tools such as n8n, Power Automate, Zapier, or custom scripts to streamline repetitive tasks in the implementation lifecycle. - Integrate outputs with system APIs to populate configuration templates and system admin screens. - Partner with subject matter experts to identify high-impact use cases and translate business needs into scalable technical solutions. - Collaborate with Product and Engineering teams to ensure solutions are secure, compliant, and maintainable. - Create internal documentation, training materials, and guides to support adoption and enable team self-sufficiency. - Stay current on AI/automation trends and proactively propose new tools or approaches that can drive efficiency. Qualifications - Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field; or equivalent practical experience. - 3+ years of experience in a role focused on automation, AI/ML, or software development. - Hands-on experience with workflow automation platforms (e.g., n8n, Power Automate, Zapier). - Experience working with Large Language Models (LLMs) like OpenAI GPT, Claude, or similar. - Strong understanding of REST APIs, JSON, and systems integration concepts. - Proficient in JavaScript, Python, .net or other scripting languages used for automation. - Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and security best practices. - Excellent problem-solving skills and ability to work independently on ambiguous or evolving projects. - Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications - Experience working in the mortgage or fintech industry, particularly in implementation or configuration roles. - Familiarity with Loan Origination Systems (LOS), especially Mortgage Cadence. - Experience with document parsing, data extraction, and AI-based content analysis. - Exposure to RPA tools such as UiPath, Automation Anywhere, or Blue Prism is a plus. - Knowledge of prompt engineering techniques and model fine-tuning is a plus. Benefits - The opportunity to lead innovation initiatives within a dynamic Professional Services team. - Hands-on experience with the latest AI and automation technologies. - A chance to make a measurable impact on client success and internal efficiency. - Collaborative environment with a strong focus on continuous improvement and solution design.

• Build AI automations and agents end-to-end, from triggers and API integrations to LLM logic. • Integrate clients' tools: CRM, email, ads platforms, and data sources. • Harden and hand over systems with documentation, monitoring, and robust error-handling so they run at the client without babysitting. • Turn recurring patterns into reusable building blocks to speed up the setup of future systems.

• Develop and evaluate AI models to detect deepfakes and synthetic content in images, PDFs, and scanned documents • Analyze invoices and business documents for manipulation, forgery, or AI-generated alterations • Support the integration of AI-powered document verification solutions into production workflows • Research and implement state-of-the-art techniques in deepfake detection, document forensics, and generative AI • Assist in building proof-of-concepts and datasets for fraud detection and authenticity verification

• Lead the product team. Manage, develop, and grow a team of product managers. Set the bar for discovery rigor, roadmap clarity, and shipping discipline. Build the team's capability alongside the products. • Own the portfolio roadmap. Set the 12-to-18-month product strategy across AI Products.. Make the investment tradeoffs explicit. Prioritize ruthlessly across products, not just within them. • Shape the agentic experience. Define how agentic workflows reason over the Commercial World Model and the Judgment Ontology: what they assess, how they explain their work, and where they hand off to a human analyst. The user's trust in the output depends on the quality of the provenance chain you design. Evaluation frameworks (how we measure whether agentic outputs are correct, complete, and defensible) are a first-order product concern. • Drive discovery with enterprise customers. Work directly with investigators, compliance officers, supply chain teams, and intelligence analysts at Fortune 500 enterprises, financial institutions, and government agencies. A customer advisory board and structured discovery process are already in place. You will use them and make them better. • Partner with engineering and design. Work closely with ML engineers, platform engineers, and the design team to understand the capabilities and constraints of our agentic architecture. Make sound product decisions at the model layer and the infrastructure layer, not just the interface. • Enable GTM. Build the product knowledge that sales and solutions engineering need to close enterprise deals. You will be in the room for late-stage evaluations. • Measure outcomes. Product analytics and an AI-based product team operating system are already in place. Define the metrics that tell you whether the portfolio is working. Use them to make decisions, not decorate reviews.