• Lead the design and implementation of complex ML/AI systems end-to-end, owning architecture decisions and driving solutions from research through production at scale • Build and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment across teams • Set the standard for AI-forward engineering, using tools like Claude and Cursor with sophistication and helping the team adopt them effectively • Partner with product, engineering, and leadership to shape AI strategy and align technical direction with business outcomes • Translate complex AI tradeoffs, risks, and opportunities into clear narratives that drive decision-making across technical and non-technical stakeholders • Lead design reviews and technical discussions, raising the bar for engineering rigor and constructive challenge across the team • Define AI architecture and engineering standards, bringing depth on tradeoffs, long-term implications, and responsible AI practices • Mentor and grow junior and mid-level engineers, multiplying impact through coaching, code reviews, and pairing on hard problems • Take ownership of the most ambiguous and highest-stakes pieces of work, driving them through to production with care for reliability, cost, and safety.

• Design, develop, and operate large-scale, high-performance infrastructure that powers Confluent Cloud. • Build foundational software to improve reliability, scalability, and efficiency across cloud environments. • Work on distributed systems challenges such as consensus algorithms, failover strategies, and resource allocation. • Collaborate with teams across Confluent to optimize and enhance infrastructure for real-time data streaming use cases. • Troubleshoot and improve system reliability, observability, and performance across multiple cloud providers (AWS, Azure, GCP).

• Design, implement and deliver scalable AI-centric software systems. • Drive the development of agentic AI capabilities for identifying vulnerabilities, automating penetration testing processes, workflow optimization and enhancing threat intelligence. • Own and drive the end-to-end development of product features from ideation to production deployment and monitoring. • Actively contribute to and drive the design and implementation of AI-enabled systems, promoting effective SDLC processes. • Lead technical discussions, code reviews and design sessions, sharing your expertise to uplift the team's capabilities. • Provide mentorship and support to junior engineers, encouraging professional growth and development. • Collaborate closely with cross-functional teams to integrate AI capabilities into broader systems and applications.

• Set and lead the storytelling strategy for Pfizer’s AI-native engineering transformation, translating platform capabilities and engineering impact into narratives that resonate across the organization and shape how executive leadership understands the value being created. • Define and lead the strategic approach to high-impact live moments (showcases, demo days, and events) that put builders’ work in front of peers and senior stakeholders • Deliver a regular cadence of flagship storytelling pieces that raise the visibility and credibility of the team’s work and influence executive leadership’s continued confidence and investment. • Establish and lead a systematic communications operating model across the organization, including a shared content calendar, reliable content-sourcing pipelines from engineering teams, and clearly defined roles and responsibilities within the team. • Own the storytelling and communications budget, resourcing a core team supplemented by contract talent to deliver exceptional creative output. • Directly lead, coach, and develop a high-performing storytelling team, complemented by contract and agency talent. Setting clear goals and priorities, managing performance, and building the team’s bench strength and capabilities over time. • Own the creative agency relationship lifecycle. From sourcing and selection through briefing, creative direction, and ongoing performance management to ensure external partner consistently deliver exceptional work. • Apply an audience-first approach to content strategy, tailoring formats, channels, and creative execution to the preferences and needs of each target audience, from individual engineers to the executive leadership team. • Build and leverage strong relationships across engineering and senior leadership to source stories directly from the work, understanding what is being built, for whom, and why it matters. Use that insight to shape strategic communications priorities. • Establish and track success measures focused on builder engagement, community growth, and leadership confidence, and use these insights to inform team strategy and continuous improvement. • Anticipate and manage the organizational change involved in shifting how Pfizer engineers work and are perceived, preparing engineering and business stakeholders across the organization for new ways of working.