Staff AI Engineer – Agentic AI and Automaton

<div class="content-intro"><p>At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design.</p></div><h3><strong>About the Role:</strong></h3> <p>We are looking for a seasoned Staff Engineer to lead the design and delivery of highly scalable, cloud-native backend, data, and AI systems with a strong focus on AI-driven automation and agentic workflows.</p> <p>In this role, you will define the technical direction for the core TPA platform (Eligibility, Provider Data and others), enable intelligent, end-to-end workflows across systems, and drive the integration of AI into real-world business operations. You will operate at the intersection of backend architecture, data engineering, and applied AI, while mentoring engineers and influencing technical strategy across teams.</p> <p>This is a hands-on leadership role for someone who thrives in ambiguous, high-impact problem spaces and can translate emerging AI capabilities into production-grade systems at scale.</p> <h3>What you'll do:</h3> <ul> <li>Set the technical vision and drive architecture for scalable, cloud-native backend, data, and AI systems</li> <li>Design and build API-first and event-driven systems supporting internal and external integrations (partners, EDI, downstream platforms)</li> <li>Lead development of high-throughput data pipelines (batch + streaming) powering operational workflows and AI use cases</li> <li>Design and implement AI-driven automation and agentic workflows to reduce manual operations and enable intelligent decisioning</li> <li>Integrate LLM-based capabilities (search, summarization, copilots, workflow orchestration) into core platform services</li> <li>Establish best practices for AI systems (prompting, evaluation, guardrails, observability, responsible AI)</li> <li>Build and evolve integration layers across APIs, events, and file-based systems (including complex partner integrations)</li> <li>Improve data quality, validation, lineage, and real-time visibility across critical business workflows</li> <li>Drive adoption of AI-assisted development workflows (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate engineering velocity and delivery</li> <li>Partner with Product, Data, and Operations to translate complex workflows into scalable, intelligent systems</li> <li>Lead small but nimble teams, cross-team initiatives, influencing technical roadmap and AI adoption and implementation strategy</li> <li>Mentor sr. engineers and technical leads, raising the bar on system design, data engineering, and AI adoption</li> </ul> <h3>To be successful in thi