• Drive and close instrument orders and proactively propose the solutions best suited to your clients' needs • Manage opportunities and sales cycles for in-house diagnostic analyzers in the region • Collaborate with veterinary diagnostic consultants by providing technical expertise to both consultants and clients • Proactively initiate and coordinate lead generation for analyzers • Assume sales administration responsibilities, including creating and maintaining account profiles • Continuously acquire and develop technical knowledge of products and services, technologies, operations, and processes

• Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges • Implement and optimize RAG systems for production use cases • Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor. • Support presales: discovery calls, technical proposals, scoping, and client-facing demos • Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team • Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs • Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools. • Deploy ML and LLM-based solutions • Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking. • Lead architecture reviews, produce technical design documents, and contribute to standards • Mentor engineers, lead code reviews, and share knowledge across the team.

• Customer Engagement: Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions. In this role you will split your time evenly between billable and pre-sales activity. • Technical Leadership: Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives. • Pre-Sales Support: Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings. • Project Oversight: Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes. • Solution Design: Architect data solutions, incorporating best practices in data governance, security, and quality. • Data Analysis: Evaluate data sources for their value, recommending data inclusion strategies to enhance analytical processes. • Cross-Functional Collaboration and Leadership: Lead internal teams, provide direction and mentorship to project teams to deliver solutions and educate end users on data products and analytic environments. • Problem Resolution: Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections. • Quality Assurance: Test data movement, transformation code, and data components to ensure accuracy and reliability.

• Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions. • Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives. • Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings. • Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes. • Architect data solutions, incorporating best practices in data governance, security, and quality. • Evaluate data sources for their value, recommending data inclusion strategies to enhance analytical processes. • Lead internal teams, provide direction and mentorship to project teams to deliver solutions and educate end users on data products and analytic environments. • Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections. • Test data movement, transformation code, and data components to ensure accuracy and reliability.