• Have advanced knowledge about the Synapse Select product line, including deployment methods and deployment architecture for both on-premise and cloud configurations • Create, maintain, and execute manual Software test cases for Verification and Validation protocols for the Synapse Select product line • Occasional exploratory functional testing and ticketing of any issues found • Reproduce and document any product defects and/or reported bugs in the JIRA development ticketing system. • Execute individual development ticket and regression testing with clear documentation of test results. • Correspond with Software and Template Engineering, give feedback to any questions they may have, and facilitate the provision of more information if needed • Work with contractor QA team(s) on the grooming of development tickets and answer any questions they may have • Participate in calls with the automated testing team for reviewing implementation of new test cases and give feedback for improvement of the protocol • Create, Design Forms as required by the Medical Informatics Design Control Process for Synapse Select products as needed. • Occasionally help to address Corrective and Preventive actions (CAPA) assigned to Synapse Select as needed and complete in a timely manner. • Help to develop, document, and occasionally conduct internal technical trainings regarding new development for the Synapse Select product line. • Assist the Medical Informatics documentation team in the creation and maintenance of service manuals and product documentation for Synapse Select. • Assist Operations and Support with technical questions related to the Synapse Select product line. This may include attending customer meetings and additional items as necessary. • Additional responsibilities as defined by management.

• Provide direct Customer Advocacy support by conducting hands-on investigations of reported device malfunctions. • Perform failure analysis and work with software engineers to determine root causes. • Collaborate and communicate with interdepartmental groups—including Regulatory, Quality Assurance, R&D, and Process Engineering—to provide documentation and operational support for device malfunction issues. • Design, improve, and implement complaint investigation processes. • Understand the technical architecture of internally developed applications. • Utilize structured problem‑solving and drive engineering studies using standardized methodologies and statistical data analysis. • Ensure documentation is updated to reflect changes made to a process or product. • Track failures or enhancement requests.

• Driving Comprehensive Safety Assessments: Execute civil safety assessments in accordance with ARP4761 or military safety assessments per MIL-STD-882E. This includes developing System Safety Program Plans (SSPPs), Functional Hazard Assessments (FHAs), Fault Tree Analyses (FTAs), and Safety Assessment Reports (SARs). • Shaping Design Requirements: Collaborate with systems, hardware, and software engineering teams to define safety-critical requirements during the development process. • Reviewing & Refining Designs: Dive deep into design documentation for safety-critical systems, providing expert analysis and feedback to ensure the highest standards of safety. • Mentorship & Leadership: Share your expertise with less experienced engineers, guiding them in safety practices and fostering a culture of continuous learning. • Cross-Team Collaboration: Partner with customers, stakeholders, and organizational leaders to develop plans, solve challenges, and deliver excellence. • Have a self-starter mindset, eager to learn, adapt, and contribute to a positive and innovative work environment. • Use your outstanding communication skills to translate technical issues into actionable insights for a variety of audiences. • Use your exceptional problem-solving skills and a drive to tackle complex, dynamic challenges.

• Design Generative AI systems leveraging GANs, VAEs, and transformer-based models for content synthesis, simulation, and data augmentation • Architect Agentic AI frameworks using Lang Chain, Hugging Face, GCP Agent space, Azure AI Foundry, AWS Bedrock, and vector databases to enable autonomous problem-solving and adaptive learning • Implement Agentic Mesh ecosystems where AI agents collaborate dynamically, combining language, behavioral, and domain-specific capabilities • Develop novel techniques for LLM/SLM fine-tuning, including retrieval-augmented generation (RAG) and context-aware prompt engineering • Optimize inference performance for real-time applications using MLOps pipelines and cloud-native deployment using native PaaS • Collaborate with high-performance teams to deploy AI systems that redefine industry standards.