• Develop and support HL7 interfaces for the Epic EHR and ancillary systems • Design, build, test, and deploy interfaces using Epic Bridges and HL7 standards • Monitor and maintain interface performance, ensuring data integrity and timely message processing • Troubleshoot and resolve interface errors, message failures, and data discrepancies • Perform HL7 message mapping, transformation, and validation (ADT, ORM, ORU, SIU, etc.) • Review Epic release updates and implement required interface changes • Support interface engine maintenance, upgrades, and enhancements • Collaborate with internal teams and vendors to support integrations and resolve issues • Maintain accurate and up-to-date interface documentation and standard operating procedures • Participate in system testing, including unit, integration, and user acceptance testing • Ensure compliance with healthcare data standards, security, and interoperability requirements

• Assist MMS (Medical Management Systems) with Field Action execution, including customer notifications, obtaining customer acknowledgment forms, and follow-ups with customers to answer questions • Install and support the deployment of BD servers and software in customer environments • Communicates technical requirements and recommendations/solutions to customers and project leadership team • Demonstrate understanding of hospital information systems, system validation, active directory, databases, and system virtualization, cloud technologies • Lead customer teams, share expertise, gain consensus within teams and deliver concise and consistent communication • Demonstrate problem solving, troubleshooting, and system consultation related to BD products, best practice considerations and standardization • Comply with all Central Server & Software Deployment Policies and Procedures • Monitor and supply updates on escalated critical issues • Recognize unnecessary workflow steps and identify processes that can be improved to increase efficiency • Follow and provide feedback on technical documentation, new product validation/requirements, product documentation, test plans, technical solution design, server & software deployment, system integration etc.

• Modernize and fine-tune our IT systems to ensure they securely and efficiently support autonomous and agentic AI workflows. Build reliable, scalable automation infrastructure that significantly enhances team efficiency and reduces manual work. • Partner with the Director of AI Enablement & IT to operationalize AI initiatives using tools like Claude, ChatGPT, and Zapier. Design intelligent workflows that connect platforms like Google Workspace and Slack, allowing AI agents to trigger real, multi-step actions. • Administer and optimize core IT domains, including Identity Providers and Mobile Device Management. Leverage advanced features like Okta Workflows to streamline identity and access operations. • Deploy across various departments to assist directly with the technical rollout of AI enablement projects. • Manage and streamline our broader SaaS stack, including Google Workspace, Linear, and tens of other applications. • Assist in creating playbooks and training resources to help teams adopt new AI tools seamlessly into their existing workflows.

• Help support our emerging product, Night Shift, an AI research assistant that amplifies the impact of investigators by automating the tedious, repetitive steps involved in working a case. • Work closely with partners in Engineering (Backend, Frontend, and Design) in a fast-paced environment. • Be one of the earliest technical contributors to our system architecture for agentic AI, and will own our AI evaluation framework. • Achieve measurably faster, more accurate leads for every officer and every shift. • Immerse yourself in the current system design and agent/tooling landscape. Understand the core customer use cases and data flows. • Support the team by shipping a few quick wins (e.g., refining tool APIs, prompt engineering, fixing bugs). • Stand up the foundational eval and observability scaffolding (datasets, metrics, KPIs, reporting). • Propose a technical architecture and implementation plan for an agent evaluation framework. • Deliver the MVP evaluation harness to produce initial metrics, enable debugging and perform regression testing. • Take on a system feature that offers demonstrated improvement against your MVP evaluation suite. • Productionize the evaluation and observability platform and make it the source of truth for quality and safety.