Join Reflection AI as a Distributed Systems Engineer to build foundational platforms for open intelligence systems.
Posted by employer 1 month ago
First seen on Joblaze 2 months ago
Last verified on the company career page 20 hours ago
Requirements
Not disclosed in this posting: compensation, years of experience, work arrangement.
Benefits
Joblaze summary
In this role, the engineer focuses on building and maintaining the foundational platform that supports various teams in their research and production efforts. Key skills include expertise in distributed systems, service development using languages like Go and Rust, and a strong understanding of reliability engineering principles. This position is ideal for experienced software engineers who thrive in dynamic startup environments and are eager to tackle new challenges. Reflection AI emphasizes collaboration and innovation, making it a fitting place for those passionate about advancing open AI technologies.
Joblaze insights
Quick facts
From the original posting
Build and operate a company-wide foundations platform that accelerates every team by providing reliable, scalable developer infrastructure, SRE capabilities, and high-throughput data ingestion tooling enabling Reflection to move faster as we scale.
Build and operate the core shared services that power our research, training, and production environments. These systems form the foundational platform that multiple teams depend on for model development, deployment, and evaluation, unifying data, compute, and workflow management across the stack while enabling rapid experimentation and reliable production systems.
Build and operate shared services that multiple teams rely on across research and production workflows.
Define and uphold reliability targets through SLIs, SLOs, and healthy on-call practices.
Maintain strong operational readiness with runbooks, incident playbooks, and capacity planning.
Ensure correctness and performance under load, addressing consistency, tail latency, and failure modes.
Develop APIs, SDKs, and internal platforms that enable high-velocity experimentation and iteration.
Reduce operational burden through better tooling, standardization, and platform patterns that scale across teams.
Container Abstractions: Containers-as-a-Service, Kubernetes abstraction layers, container orchestration, reproducible environments, multi-tenant isolation.
Distributed Systems Architecture: Sharding, replication, coordination services, high-concurrency systems, concurrency control.
Service Development Stack: gRPC, Protobuf, Go, Rust, C++.
Reliability & Performance: Idempotency, retries, backpressure, SLI/SLO design, tail latency optimization, service reliability engineering.
Strong software engineering background with experience shipping production-grade systems.
Experience designing APIs, services, or developer platforms that handle large-scale data or compute.
Comfortable navigating complex codebases, debugging hard problems, and optimizing for reliability and speed.
Thrive in a high-agency, fast-paced startup environment; bias toward action and impact.
Excited about zero to one challenges, building new systems rather than maintaining legacy ones.
Collaborative, clear communicator, and comfortable working across research and infra boundaries.
Motivated by creating the software backbone for the world’s most capable open-weight AI systems.
Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
Standard company text repeated across Reflection AI's postings is omitted here.