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Senior, highly specialized platform role at a strong brand reduces applicant competition.
Deep infrastructure and distributed-systems expertise required, limiting cross-industry transferability.
Explicit 15+ years and principal-level distributed-systems/Kubernetes requirements enforce high shortlisting strictness.
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Own the long-term technical architecture and make critical build vs. buy decisions to ensure platform scalability and resilience at 10x scale.
Design, develop, and maintain core infrastructure services and microservices supporting ML, frontend, and platform teams, writing production-grade code across the stack (K8s, Python, Golang, Postgres).
Drive business-critical engineering outcomes aligned with business goals, engineering velocity, system reliability, and infrastructure cost, while mentoring senior engineers and fostering engineering excellence.
15+ years of software engineering experience with progression into Principal or Sr. Staff Engineer at a high-growth tech company or top-tier AI lab.
Strong hands-on coding proficiency with system-level architecture experience; preferred experience in K8s, Python, Golang, Postgres, and data lakes.
Proven experience in distributed systems focusing on performance, scalability, latency, optimization, and monitoring.
Experience integrating AI into workflows or decision-making; ability to connect engineering decisions to business outcomes (e.g., latency improvements, margin efficiency).
Senior engineer capable of both strategic architecture and detailed code-level execution in a scalable, fast-growing technology environment.
Experience working in high-growth startups or AI-driven tech organizations with a commercial mindset connecting engineering efforts to business impact.
Demonstrated high ownership and initiative at startup pace, with experience collaborating cross-functionally and mentoring senior technical staff.