• Lead the design and implementation of core components of the Libraries Platform including the services, pipelines, and package index that power secure, reproducible build, test, and distribution workflows for libraries across multiple ecosystems (Java, JavaScript, Python/AI/ML). • Design and maintain automation for artifact creation, updates, and verification, including vulnerability scanning, remediation workflows, SBOM and provenance generation, and policy enforcement across our library catalog. • Build toward novel patch generation. Develop and validate automation that generates security fixes — including AI-assisted patching — rather than only applying upstream patches, with the testing and verification needed to trust the result. • Build and operate shared platform services such as package indexes, registry mirrors, metadata services, and orchestration tooling that serve both external customers and internal ecosystem teams. • Develop internal developer tools and CLIs (often in Go) that improve how we build, test, and ship libraries at scale, including integration with build systems and CI/CD for multiple ecosystems. • Drive reliability, scalability, and observability for the Libraries platform: define SLOs, build monitoring and alerting, and lead incident response and post‑incident improvements. • Solve complex dependency and build issues in production environments, from toolchain and compiler problems to CI/CD flakiness and registry/package index edge cases. • Partner closely with ecosystem teams (Java, JavaScript, Python/AI/ML), Platform, Delivery, Sustaining, and Security to ensure the platform meets reliability, security, and product requirements. • Mentor and unblock other engineers through design reviews, documentation, and hands‑on debugging, helping to “code culture” into how we build and run our libraries platform.

• Manage a team of architects and scrum teams comprising architects, software engineering, and quality engineering based in the US and India. Also managing one-time investment projects with offshore scrum teams. • Operate an R&D organization with modern Event-based architectures running in Azure based on C#, SQL, COSMOS, and other Azure PaaS offerings. • Maintain and evolve the organization’s architecture strategy, principles, standards, and reference patterns across product and platform teams. • Ensure architectural oversight of modernization, Azure adoption, datacenter technologies, integration, data, security, scalability, and resiliency decisions. • Maximize teams use of AI tools to accelerate delivery. Measure productivity increase and how it ties to accelerated business objectives. • Work within a very large technology organization of 600+ running SAFe. • Serve as an engaged executive technology leader who develops engineering and architecture leaders, guides critical technical decisions, and ensures architectural direction supports product, platform, security, and operational objectives. • Set direction and maintain executive accountability for core platform capabilities—including CIAM, the enterprise data lakehouse, and shared data services—ensuring their roadmaps, adoption, reliability, security, and investment align with product and business priorities. • HR management of development team members, including hiring, performance reviews, coaching, improvement plans, and overall growth of team skills • Lead and collaborate with architects, product managers, software development managers, and developers to architect and develop the best technical design and approach, delivering value quickly to customers without sacrificing software quality • Work closely with product management, customers, other support organizations, vendors and other team members to understand the team and product needs • Have responsibility for identifying and measuring key objectives for the team, including DORA, annual goals and targets based on overall business needs of the organization • Identify and champion cross organization continuous improvement efforts starting from business value through to final implementation • Inspire and sustain team unity and engagement by developing, mentoring, motivating, and guiding the team to achieve results together through productive relationships and work • Ensure that procedures and processes are well documented, trained and adhered to by the development team members • Upscale, upskill and modernize the development teams for rapid and high quality delivery of our solutions

• Design and implement AI solutions using Azure AI Foundry, Azure OpenAI, Copilot Studio, and Microsoft Fabric • Build reusable AI services, agent frameworks, prompt registries, evaluation pipelines, MCP integrations, and tool catalogs • Establish engineering standards for enterprise AI development • Create reference architectures for agents, RAG (if required), tool calling, multi-agent workflows, and Human-In-The-Loop (HITL) workflows • Provide technical guidance on when to use Copilot, Foundry, Agentforce, ChatGPT Enterprise, Claude Enterprise, and private models • Design AI-enabled solutions leveraging OneLake, Lakehouse, Data Warehouse, Data Factory, and Power BI • Establish reusable AI-ready data patterns and provide guidance to data engineering as required • Provide guidance on monitoring, telemetry, evaluation frameworks, token tracking, cost allocation, prompt performance, and agent reliability metrics • Support deployment, rollback, versioning, and incident response • Implement prompt versioning using GitHub, agent approval workflows, model routing controls, tool access controls, and usage monitoring. Automate quality control using agents in collaboration with innovation architect • Being part of the Emerging Technology team, collaborate with other team members as well as IT and business functions • Translate business use cases into reusable technical solutions

• Design and own the data foundation behind Phoenix’s agentic commerce platform. • Turn raw commerce events into structured, decision-grade intelligence that powers autonomous payment routing, approval probability scoring, checkout optimization agents, and merchant copilots. • Architect the event models, pipelines, and data contracts that allow AI agents to observe, reason, act, and improve in real time. • Design for low latency, high correctness, replayability, and observability. • Define how intelligence is embedded into core commerce behavior and how Phoenix’s systems learn from every transaction to continuously improve merchant performance.