• Take full ownership of sales quotas and proactively work towards meeting and exceeding targets within a defined Zendesk territory. • Collaborate closely with the core sales team to develop and execute strategic plans to drive revenue growth from both existing Zendesk accounts and new business pursuits. • Build and nurture strong relationships with customers, understanding their business challenges and leveraging a value-based selling methodology. • Lead and support on approved AI POC’s. • Close collaboration with the AI & core Success teams to proactively identify expansion/cross-sell opportunities. • Act as a subject matter expert for AI solutions, empowering the sales team to excel in AI-related engagements. • You'll have ownership for enablement initiatives across an assigned territory.

As a Clinical AI Engineer at DocMe360, you will play a pivotal role in shaping the future of our clinical AI solutions for the Department of Veteran Affairs. You will lead the design, development, and implementation of advanced AI architecture and algorithms, utilizing Python as your primary programming language. Your expertise will drive the innovation of clinical AI systems at the VA, enhancing client products and streamlining operations for Veterans and clinicians. This role requires strong leadership abilities, as you will mentor engineers, collaborate with cross-functional teams, and interact with clients to understand their needs. You will also be responsible for creating AI solutions for the Department of Veteran Affairs software systems, ensuring scalability, reliability, security, accessibility and performance. Your key responsibilities include: - Designing and building clinical AI infrastructure that achieve business objectives - Leading and mentoring a team of AI engineers in developing cutting-edge AI applications - Collaborating with the product manager, UX researcher/designer and stakeholders to define AI project requirements - Researching and evaluating new AI technologies and methodologies to implement in projects - Presenting technical concepts and project updates to non-technical stakeholders - Ensuring that best practices and coding standards are maintained throughout the development process - Developing Python code and AWS infrastructure that works together to build advanced clinical AI systems You will thrive in this role if you possess: - Extensive experience with Python, including backend Python frameworks (e.g., FastAPI, Flask, etc.) - Deep understanding of AWS AI infrastructure, data structures, and data processing - Experience using the OpenAI API to interact with LLMs - Knowledge of Infrastructure-as-Code (e.g., TerraForm) - Strong experience in software architecture and system design - Previous experience working in a clinical design/delivery context - Excellent problem-solving skills and ability to work under pressure - Strong communication skills, capable of conveying complex ideas clearly and concisely - A collaborative spirit and a passion for innovation in AI technology DocMe360 Values - Delivery: Commit to a culture of honesty, transparency, unwavering integrity, and professional growth - Optimism: Invest in professional growth and well-being - Collaboration: Foster teamwork and shared expertise to achieve success - Motivation: Inspire and energize clients with passion and purpose - Exploration: Seek out opportunities for innovative technologies that align with our mission

• Architect, design, and lead the implementation of scalable, secure, and resilient infrastructure for AI/ML workloads • Full stack engineer to design and develop scalable SaaS application and services • Build and maintain the continuous integration and continuous deployment (CI/CD) pipelines specifically for AI models • Act as a subject matter expert and mentor for junior engineers • Ensure the reliability, security, and performance of AI systems • Stay ahead of industry trends and bring innovative AI solutions to the table

• Establish and coordinate KBC’s AI Centre of Excellence (AI CoE) • Enable the organization to adopt and realize value from generative AI tools and solutions • Support a formal network of “AI champions” • Deliver AI training and enablement • Provide hands-on support to the user community • Build advanced prototypes and AI-driven solutions that accelerate internal efficiency • Support developer AI enablement (GitHub Copilot) • Document standards, templates, SOPs, and “how we work” guidance for AI CoE operations, champion enablement, and solution lifecycle management.