• Hire, coach, and develop a high-performing team of Solution Engineers • Build both technical depth and consultative selling skills within the team • Foster a culture of curiosity, accountability, and continuous improvement • Establish clear performance expectations and career development paths • Partner with Sales to qualify opportunities and improve deal quality • Identify and communicate product-market fit gaps to the Product team, including timelines for future functionality or confirmation that gaps will not be addressed. • Support successful client transitions from pre-sales to implementation by establishing clear expectations, scope, and handoff processes when product-market fit is confirmed, and clients select FMX. • Ensure delivery of high-quality, tailored product demonstrations that clearly articulate value and differentiation • Validate that proposed solutions align with customer requirements, constraints, and desired outcomes. Identify risks, gaps, or misalignments early in the sales cycle • Oversee technical discovery, solution design, and validation to align with customer needs and use cases • Establish best practices for demos, proofs-of-concept, and technical presentations • Partner with RevOps and/or finance to determine the most effective use of solution engineering resources based on their impact on win rates, average deal size, deal velocity, and SaaS Magic Number (ARR for the quarter divided by sales and marketing spend for the previous quarter) • Reallocate resources and propose changes to the team, their focus, and processes to deliver improvements in win rates, average deal size, deal velocity, and SaaS Magic Number, where an SE resource(s) was utilized to the CRO via business cases • Develop and refine playbooks for discovery, demos, and solution design • Implement tools and processes to improve efficiency and consistency across the team • Drive the use of reusable assets, demo environments, and solution templates • Determine whether specific segments and bands require SE resources or whether AEs can deliver the demo using live software or demoware

• Design and implement data and application integrations using Boomi, APIs, and event-driven patterns • Build and manage secure, scalable integrations across enterprise platforms including ERP, CRM, operational systems, and data platforms • Monitor, troubleshoot, and optimize integration workflows for reliability and performance • Extract, transform, and model structured and semi-structured data for analytics and downstream consumption • Implement and manage data storage solutions including data lakes, data warehouses, and curated data marts • Partner with architects, data scientists, and business teams to design solution patterns that support AI and automation use cases • Enable AI solutions by engineering clean, well-integrated, and governed data inputs • Build and manage automated data and integration pipelines delivering consistent outcomes • Contribute to technical documentation, operational runbooks, and knowledge sharing

• Define and lead enterprise data strategy, aligning business goals, data architecture, and AI/ML adoption • Design and implement modern cloud data platforms (lakehouse, data warehouse, streaming architectures) • Establish and enforce data architecture standards • Own and define enterprise data governance frameworks, including data ownership, stewardship, lineage, metadata, and data quality standards • Establish data management operating models and governance processes across business and engineering teams • Design and build scalable, reliable, and high-performance data pipelines • Optimize data platforms for performance, scalability, and cost efficiency • Ensure data quality, consistency, and accessibility across all data layers • Enable AI-ready data platforms, ensuring governed, traceable, and high-quality datasets for analytics and ML • Conduct data maturity assessments and define transformation roadmaps • Lead client workshops, architecture discussions, and pre-sales engagements • Create and present solution architectures, proposals, and technical strategies • Act as a trusted advisor to C-level stakeholders and engineering teams • Develop reference architectures, best practices, and reusable assets • Mentor engineers and contribute to building a high-performing data engineering and architecture capability

• Engage with retail clients to understand their store operations, backend systems, and data requirements. • Define end-to-end integration strategies, including data ingestion, pre and post processing, and publishing to relevant retail systems. • Serve as the subject matter expert on Simbe’s products and offerings, including APIs, mobile apps, and business intelligence tools. • Develop pilot use cases and demos showcasing Tally’s data capture, analytics, and integration with client’s systems. • Guide the implementation process, working with internal Simbe deployment teams and client technical teams to configure integrations. • Partner with Customer Success and Product teams to build robust adoption strategies, including user training, documentation, and onboarding processes. • Act as the technical point of contact for key stakeholders, maintaining a proactive communication channel for support.