About InvoiceCloud : 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.

com . Job Details: We are seeking a highly skilled and hands-on Senior AI Engineer 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.

This is a hands-on builder role reporting to the AI Engineering Lead. 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.

Success Profile: 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. Results Driven 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.

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. Designs and implements production multi-agent orchestration, including classification, routing, authentication, and domain-specialist agents that handle real financial transactions with high reliability. Delivers against 30- and 90-day milestones, including owning an end-to-end agent or ML pipeline in production, contributing to two or more design reviews, and demonstrating domain understanding of our billing and payments context.

Takes Ownership Owns implementation of agentic pipelines, ML models, eval frameworks, and LLM integrations end-to-end, taking full accountability from design through production deployment and monitoring. Manages model versioning across multiple vertical segments using Azure ML Model Registry, ensuring traceability and stability as models move through their lifecycle. Implements MCP (Model Context Protocol) tool integrations through API gateways with authentication gating and policy enforcement, taking ownership of secure, governed access to production systems.

Works with Snowflake data to build feature stores and orchestrate scoring pipelines that write predictions back into production systems, owning the full data-to-decision pipeline. Drives Efficiency Uses AI-accelerated development tools such as Claude Code, Cursor, and GitHub Copilot as daily force multipliers, delegating multi-step tasks to iterate three to five times faster. Establishes an AI-accelerated development workflow within the first 30 days, and becomes a recognized power user of these tools by 90 days, sharing patterns and best practices with the team.

Implements token-level cost optimization and efficient prompt chains to keep production LLM workflows performant and cost-effective at scale.