• Lead by doing - foster and build a team culture that promotes our value of “Plan, Do, Learn and Improve” and be an active contributor to the development of our platform applications. • Recruit, develop, and retain top engineering talent. • Conduct regular 1:1s and performance reviews to support growth and development. • Lead the design, development, and vision for platform applications and codebases. • Ensure projects are delivered on time, within scope, and aligned with company objectives. • Drive agile processes and establish best practices for engineering workflows. • Collaborate with Product Management, Tech Leads, and Design teams to define technical requirements and product roadmaps. • Guide the team in architecture and technical decisions to increase efficiency towards building pixel perfect applications.

• Serve as a primary platform owner for Sigma, ensuring reliability, performance, secure configuration, and smooth day-to-day operation across multiple Qventus solutions. • Interact regularly with BI vendors, including Sigma, to understand their feature roadmap and how it will impact our ability to provide next-generation analytics to our customers • Develop and maintain reusable Sigma assets, including templates, components, data models, and governance patterns, that allow analytics teams to build consistently and efficiently. • Partner with data engineering teams to ensure dbt pipelines and data models are optimized for downstream analytics consumption • Create and implement standards for dashboard performance and integrity across the analytics platform • Contribute to cross-solution deployment strategies to ensure analytics scale reliably and consistently • Participate in the evaluation and support of AI-assisted analytics tooling, semantic layer technologies, and emerging self-service analytics platforms • Prototype, test, and document new analytics features or AI-driven enhancements that could improve user experience, accelerate insights, or reduce manual effort • Provide technical thought leadership on long-term platform evolution, architectural choices, and cross-tool integration • Provide team leadership in ways that inspire and can help guide others on the team

• Lead scoping and execution of critical improvements to our data platform • Support production ML Ops functionality • Partner strategically with data science, analytics, and data engineering leads • Provide expertise on overall data engineering best practices • Support solution development; translate product / analytical vision into highly functional data pipelines

• Build and operate the LLM Platform: Develop model routing, prompt registry, and orchestration services for multi-model workflows. • Integrate external LLM APIs (OpenAI, Anthropic, Mistral) and internal finetuned models. • Enable fast, safe experimentation: Implement automated evaluation pipelines (offline + online) with golden sets, rubrics, and regression detection. • Support CI/CD for prompt and model changes, with rollback and approval gates. • Collaborate cross-functionally: Partner with product pods to instrument RAG pipelines and prompt versioning. • Work with deep learning and data teams to integrate structured and unstructured retrieval into LLM workflows. • Optimize performance and cost: Profile latency, token usage, and caching strategies. • Build observability and monitoring for LLM calls, embeddings, and agent behaviors. • Ensure reliability and safety: Implement guardrails (toxicity, PII filters, jailbreak detection). Maintain policy enforcement and audit logging for AI usage.