Senior AI Engineer

<div class="content-intro"><p><strong>About InvoiceCloud</strong>:&nbsp;</p> <p><span data-olk-copy-source="MessageBody">InvoiceCloud is a fast-growing fintech leader recognized with 20 major awards in 2025, including USA TODAY and Boston Globe Top Workplaces, multiple SaaS Awards wins for Best Solution for Finance and FinTech, and national customer service honors from Stevie and the Business Intelligence Group. Judges also highlighted our mission to reduce digital exclusion and restore simplicity and dignity to how people pay for essential services, as well as our leadership in AI maturity and responsible innovation. It’s an award-winning, purpose-driven environment where top talent thrives. To learn more, visit <a href="http://www.invoicecloud.com/">InvoiceCloud.com</a>.&nbsp;</span></p></div><p><strong>Job Details:</strong></p> <p>We are seeking a highly skilled and hands-on <strong>Senior AI Engineer</strong> to join a small, high-impact team building the AI foundation that powers the next generation of our platform, including multi-agent systems, ML scoring models, and LLM-powered products that serve millions of payers. You’ll design, build, and ship production AI that directly drives revenue and customer experience.</p> <p>This is a hands-on builder role reporting to the AI Engineering Lead. You’ll own implementation of agentic pipelines, ML models, eval frameworks, and LLM integrations end-to-end on Azure using Python and .NET, and use AI-powered development tools like Claude Code and GitHub Copilot as daily force multipliers to iterate faster. This role is based in our Boston office, working hybrid with three days in-office per week.</p> <p><strong>Success Profile: </strong></p> <p>This role is anchored in our company’s core competencies—These competencies reflect the mindsets and behaviors that define success in this role. We outline how each competency translates into real-world actions and outcomes specific to this role.</p> <p><strong>Results Driven</strong></p> <ul> <li>Owns end-to-end delivery of agentic pipelines, ML models, and LLM integrations on Azure, shipping a first production feature or pipeline contribution within the first 30 days.</li> <li>Builds end-to-end ML pipelines on Azure ML, covering feature engineering, model training for propensity, adoption, and anomaly detection use cases, offline batch scoring, and drift monitoring, to deliver measurable improvements in model accuracy and pipeline throughput.</li> <li>Designs and implements production multi-agent orchestration, including classification, routing, authentication, and domain-specialist agents that handle real financial transactions with high reliability.</li> <li>Delivers against 30- and 9