AI Engineer - Lead

Brief Description The Team: At Kind Lending, our family of diverse and talented Kind Ambassadors is the driving force behind our new approach to the mortgage experience. Our Kind Ambassadors are the heart and soul of the organization and our "People Before Profits" mentality shines through in every department. Kind Lending is growing and is looking for top mortgage professionals who value opportunity, lasting business partnerships, and who live out our KIND mindset. Kind Lending is determined to provide the best service in the industry while also providing homebuyers with a great selection of products to enhance their buying experience. Backed by our trusted leadership team, Kind Lending's friendly and professional model puts the "fun" in funding. Position Summary We are seeking a highly skilled Lead AI Engineer to design, build, and deploy intelligent automation solutions across the mortgage lifecycle. In this role, you will set technical direction for AI-powered agents, orchestrate process workflows using AI workflow tool(s), MCP, AWS Step Functions, and Lambda, and leverage a multi-cloud AI stack (OpenAI, Anthropic, GCP, Microsoft Azure) — including tools like Devin — to build scalable, cloud-native automation systems. You'll lead by example — architecting solutions, mentoring engineers, and partnering closely with business stakeholders to transform traditional mortgage processes into seamless, intelligent experiences. Responsibilities AI Agent Development • Lead the end-to-end design, delivery, and deployment of autonomous and semi-autonomous agents (agentic workflows) that interact with internal systems and users across the mortgage value chain. • Architect robust, context-aware AI agents capable of handling document analysis, decision support, data extraction, and customer engagement. • Reverse engineer existing systems, legacy workflows, and undocumented business logic to identify automation opportunities and design agent-based replacements. • Set best practices and technical standards for agent design across the team. Workflow Orchestration & Integration • Architect cloud-based process flows using AI workflow tool(s), MCP, AWS Step Functions, and Lambda, integrating AI components, APIs, and mortgage software platforms (e.g., LOS, CRM, POS). • Automate multistep business logic and exception handling with serverless functions, event-driven triggers, and low-code orchestration tools. • Design modular, scalable workflows that enable rapid iteration, monitoring, and reliability across pipelines. • Evaluate, leverage, and integrate third-party AI solutions and platforms to accelerate delivery and extend internal capabilities. AI Implementation • Leverage OpenAI, Anthropic (Claude), GCP, and Microsoft Azure AI services to build, fine-tune, and deploy AI capabilities across a multi-cloud environment. • Utilize Devin and similar AI-assisted development tools to accelerate engineering workflows. • Integrate custom and pre-trained LLMs to automate mortgage underwriting processes — document classification, condition management, intelligent routing, and dynamic content generation. • Evaluate and recommend new models, frameworks, and tools as the AI landscape evolves, including build-vs-buy decisions on third-party AI solutions. Data Analysis • Perform exploratory data analysis on structured and unstructured mortgage data to identify automation opportunities and validate agent performance. • Use data-driven insights to guide agent design, workflow optimization, and prioritization. Leadership & Collaboration • Partner with business SMEs, product managers, and data teams to map out automation targets and rapidly iterate on solutions. • Mentor mid-level and junior engineers; conduct code reviews and uphold engineering standards. • Maintain documentation and ensure compliance with data privacy and regulatory standards. • Champion a "vibe coding" approach where appropriate — using AI coding assistants (e.g., Devin) to rapidly prototype and iterate. • Stay ahead of market developments in AI, LLMs, and mortgage technology, and translate relevant trends into team roadmap decisions. Qualifications • 8+ years of professional experience in AI application development, automation engineering, or full-stack cloud engineering, including prior technical leadership. Proven Hands-on Experience With • • Agentic frameworks for building intelligent task-planning and decision-making agents. • Reverse engineer existing systems and processes to inform automation and agent design. • Evaluating, leveraging, and integrating third-party AI solutions into existing systems and workflows. • AI CLI-based development for interacting with LLMs, orchestrating workflows, and managing automation pipelines. • AI workflow tool(s) (e.g., low-code/no-code orchestration platforms), MCP, and AWS Step Functions. • OpenAI, Anthropic (Claude), GCP, and Microsoft Azure AI/ML services. • AWS Lambda and serverless architecture. • Devin or s