• Receive tasks from the Project Lead or Team Lead (TL), prepare functional and design specifications, and align them with all stakeholders • Ensure assigned areas are delivered on time and meet quality expectations • Provide effort estimations, agree on timelines with the manager, and contribute to project planning • Evaluate existing data systems and identify improvement opportunities • Develop best practices for data coding to ensure system-wide consistency • Update and optimize local and metadata models • Assess implemented data systems for discrepancies, variances, and performance efficiency • Troubleshoot and optimize data infrastructure and pipelines • Understand business drivers and analytical use cases, translating them into reliable data products • Design, implement, and maintain cloud-based pipelines that deliver business-critical data efficiently • Identify area-level risks and implement mitigation plans • Report readiness/quality status and escalate critical issues appropriately • Take responsibility for resolving crisis situations within the assigned area of responsibility (AOR) • Initiate and conduct code reviews, and help establish coding standards, conventions, and guidelines • Propose technical and functional improvements to enhance the product • Continuously upgrade professional knowledge and skills • Collaborate closely with cross-functional teams.

• Define and drive the global demand generation approach • Lead customer lifecycle marketing programs • Own net new pipeline generation across target accounts • Drive the performance of the demand generation engine

• Support for critical production applications • Analysis and resolution of P1/P2 incidents • Advanced troubleshooting and root cause identification • Emergency fixes and production deployments • Monitoring of applications and infrastructure • Participation in war rooms and crisis management • Collaboration with infrastructure, DevOps, and business teams • Contribution to performance and stability improvements • Support for technology modernization and architectural evolution • Documentation of incidents and procedures • Technical mentoring for less experienced colleagues

• Diagnose and prioritize the most impactful foundational investments across the Super Agent backend, partnering with engineering leadership to sequence them against product delivery • Own the hardest cross-cutting system problems, from architectural decomposition to cross-team interface design, going deep hands-on when the problem demands it • Build shared understanding of system health and risk across the team, helping establish the frameworks and observability needed to make investment decisions with confidence • Raise and maintain our engineering quality bar through pragmatic standards, guardrails, and team practices that prevent regressions and keep code healthy over time • Collaborate with peers across customer, product, and engineering to deeply understand customer needs, make pragmatic tradeoffs that maximize impact, and align on engineering reality • Mentor engineers as a senior peer and force multiplier, sharing expertise across backend architecture and system design while helping shape stronger engineering judgment, more effective collaboration, and a higher-performing team • Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow • Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale • Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably