We are looking for a Technical Lead to drive the architectural direction and engineering excellence of this group. This is a senior, deeply hands-on role for a technology leader who can own the technical roadmap, mentor a team of elite engineers, and build the infrastructure that challenges platform to its theoretical limits.
What You'll Lead:
Define and own the technical architecture of the group's distributed testing and reliability platform – designing for massive scale, real-world workload simulation, and adversarial failure injection
Lead effort involving multiple engineers, setting technical standards, running architecture reviews, driving design decisions, and mentoring engineers to grow
Build the systems that orchestrate millions of concurrent IO operations, inject chaos at the infrastructure layer (latency, packet loss, hardware failures), and expose the hardest-to-find race conditions and consistency bugs
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Drive observability and reliability engineering across the group – building telemetry pipelines that track P99 latency, jitter, and system health, turning quality into a quantitative discipline
Collaborate deeply with Core R&D, Storage Kernel, and Infrastructure teams – translating architectural knowledge into targeted reliability strategies
Establish engineering practices – design docs, production-grade code reviews, testing philosophy, and cross-team technical alignment
What You'll Lead:
Define and own the technical architecture of the group's distributed testing and reliability platform – designing for massive scale, real-world workload simulation, and adversarial failure injection
Lead effort involving multiple engineers, setting technical standards, running architecture reviews, driving design decisions, and mentoring engineers to grow
Build the systems that orchestrate millions of concurrent IO operations, inject chaos at the infrastructure layer (latency, packet loss, hardware failures), and expose the hardest-to-find race conditions and consistency bugs
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Drive observability and reliability engineering across the group – building telemetry pipelines that track P99 latency, jitter, and system health, turning quality into a quantitative discipline
Collaborate deeply with Core R&D, Storage Kernel, and Infrastructure teams – translating architectural knowledge into targeted reliability strategies
Establish engineering practices – design docs, production-grade code reviews, testing philosophy, and cross-team technical alignment
Requirements:
Strong software engineering background with 6+ years of hands-on Python development experience is required. The ability to read, debug, and reason about C++, Rust, or Go is a significant advantage
Deep understanding of distributed systems: concurrency, consistency models, fault tolerance, and large-scale system behavior under stress
Background in one or more of: storage systems, networking (TCP/IP, RDMA), cloud infrastructure, database internals, or high-performance backend systems
Experience building large-scale infrastructure platforms, internal developer platforms, or reliability engineering systems
Leadership:
Proven track record leading complex technical initiatives from architecture through delivery
Experience mentoring and growing engineers – raising the technical bar of a team, not just directing work
Ability to drive technical alignment across teams, communicate tradeoffs clearly, and make high-quality architectural decisions at speed
Comfortable operating at both the strategic and hands-on level – you write code, review designs, and shape roadmaps
Previous experience in people management roles – Advantage
Mindset:
You approach quality through the lens of Site Reliability Engineering: you care about MTTD, observability, and building self-healing systems
You have a "hacker" instinct – you don't just find bugs; you find the architectural flaws that allowed them to exist
You are an early adopter of AI tools and excited about applying LLMs and generative AI to accelerate engineering velocity
Big Advantages
Experience with storage systems, file systems, or high-performance distributed environments
Background in chaos engineering, fault injection, or simulation systems
Familiarity with observability tooling and performance engineering at scale
Experience building testing or reliability platforms as first-class engineering products
Prior experience as a Team Lead in a high-growth infrastructure company
Strong software engineering background with 6+ years of hands-on Python development experience is required. The ability to read, debug, and reason about C++, Rust, or Go is a significant advantage
Deep understanding of distributed systems: concurrency, consistency models, fault tolerance, and large-scale system behavior under stress
Background in one or more of: storage systems, networking (TCP/IP, RDMA), cloud infrastructure, database internals, or high-performance backend systems
Experience building large-scale infrastructure platforms, internal developer platforms, or reliability engineering systems
Leadership:
Proven track record leading complex technical initiatives from architecture through delivery
Experience mentoring and growing engineers – raising the technical bar of a team, not just directing work
Ability to drive technical alignment across teams, communicate tradeoffs clearly, and make high-quality architectural decisions at speed
Comfortable operating at both the strategic and hands-on level – you write code, review designs, and shape roadmaps
Previous experience in people management roles – Advantage
Mindset:
You approach quality through the lens of Site Reliability Engineering: you care about MTTD, observability, and building self-healing systems
You have a "hacker" instinct – you don't just find bugs; you find the architectural flaws that allowed them to exist
You are an early adopter of AI tools and excited about applying LLMs and generative AI to accelerate engineering velocity
Big Advantages
Experience with storage systems, file systems, or high-performance distributed environments
Background in chaos engineering, fault injection, or simulation systems
Familiarity with observability tooling and performance engineering at scale
Experience building testing or reliability platforms as first-class engineering products
Prior experience as a Team Lead in a high-growth infrastructure company
This position is open to all candidates.
