• Design, build, and maintain the Traffic Management System API (a Go service) to manage routing and traffic-steering configuration across our global edge fleet • Develop the agent that renders and applies routing configuration on edge nodes, reliably driving desired state from the API out to the edge • Build and extend BGP and Anycast routing capabilities, including config rendering, peer-group and route-map support, and prefix filtering, as we consolidate edge routing onto a single control plane • Develop and maintain automated failover and high-availability solutions, including non-stop maintenance mode and capacity- and health-aware traffic offloading from saturated points of presence • Strengthen reliability through strong test coverage (config rendering and end-to-end pipeline tests), metrics, and observability across the routing pipeline • Collaborate with cross-functional teams to optimize system performance, reliability, and resiliency

• Define and lead the long-term technical architecture of the platform • Lead backend architecture and infrastructure strategy using Rust-based systems • Help build scalable systems supporting feeds, messaging, live updates, video, and data infrastructure • Oversee engineering direction across backend, frontend, infrastructure, and product systems • Partner closely with leadership on product and company strategy • Establish engineering culture, hiring standards, and technical execution processes • Work directly with engineers on architecture reviews, tradeoffs, and implementation decisions • Help design future financial infrastructure including rewards, wallets, payments, and crypto-related systems • Support AI-powered systems including translation, recommendation, search, and football history infrastructure • Ensure scalability, reliability, performance, and security across all systems

• Build and operate backend systems that serve AI-powered insurance workflows in production. • Design and implement AI orchestration layers that connect models, APIs, workflows, and business logic. • Build inference pipelines for LLM-based and AI-assisted automation systems. • Optimize latency, throughput, and cost across AI services (caching, batching, streaming, routing). • Design stable service boundaries between backend systems, ML components, and product APIs. • Implement observability: logging, metrics, tracing, alerting, and incident response workflows. • Debug production issues across distributed AI systems and resolve root causes. • Collaborate closely with frontend, product, operations, and ML teams to ship end-to-end features. • Continuously improve system reliability, scalability, and performance.

• Design, develop, and own features within the core enterprise integration layer, from technical design to deployment and monitoring. • Implement event-driven solutions using Azure Service Bus and Azure Functions, aligned with the broader integration architecture. • Collaborate closely with the Principal Architect, tech leads, and other developers to deliver consistent, scalable solutions across business verticals. • Take full ownership of assigned tasks, from planning through delivery, with minimal need for oversight. • Communicate clearly and proactively with both technical and non-technical stakeholders on progress, blockers, and technical decisions. • Champion code quality, testing, and CI/CD best practices; actively participate in code reviews. • Troubleshoot and resolve complex issues in a distributed, cloud-based environment using Application Insights or equivalent APM tooling.