Core Engineering at Rox Data Corp in San Francisco, CA

ABOUT ROX Rox https://www.rox.com/?utm_source=chatgpt.com is building the AI-native revenue operating system. Most enterprise software was built for humans operating dashboards. Rox is built for agents operating systems. Instead of static workflows, Rox runs continuous decision loops powered by real-time context from across the enterprise. Agents analyze signals, reason about them, and take action — automatically. To make that possible, we are building infrastructure that combines elements of: - distributed systems - real-time decisioning - agent execution frameworks - semantic retrieval systems - low-latency streaming infrastructure - knowledge graph architectures We’re backed by Sequoia, GV, and General Catalyst and have grown rapidly from 15 to 75 people while shipping our platform years faster than the market expected. We already support Global 2000 customers across industries including banking, hardware, construction, and sovereign AI. We are building for what enterprise AI systems will require two years from now — not just what exists today. ABOUT THE CORE ENGINEERING TEAM Core Engineering builds the systems that make autonomous revenue agents reliable at enterprise scale. This team sits at the center of Rox’s long-term technical strategy and owns foundational infrastructure across: - agent reliability and orchestration - distributed execution systems - graph-based retrieval infrastructure - streaming and real-time context systems - observability for autonomous workflows - low-latency data and inference pipelines The problems here look less like traditional SaaS application engineering and more like: - real-time OLAP systems - streaming compute platforms - distributed databases - semantic retrieval systems - deterministic execution infrastructure - high-scale platform engineering At Rox, agents continuously: - retrieve context - reason across changing state - trigger actions - update workflows - coordinate across systems Core Engineering builds the infrastructure that makes those loops fast, reliable, observable, and deterministic. THE ROLE We are hiring a Core Engineer to help design and operate the foundational infrastructure behind Rox’s autonomous agent platform. This role is ideal for engineers who have deep systems intuition and want to work on infrastructure problems at the frontier of AI reliability. You might be a fit if you’ve spent time building: - distributed infrastructure - streaming systems - semantic search infrastructure - graph-based retrieval systems - execution runtimes - reliability infrastructure - low-latency backend platforms Or if you’ve historically been “the person” inside your company for difficult infrastructure problems. We care deeply about engineering craftsmanship, systems thinking, and people who can reason about long-term architecture under real-world scale constraints. WHAT YOU’LL DO - Build infrastructure for reliable autonomous agent execution - Design systems for deterministic, auditable agent behavior at enterprise SLAs - Develop low-latency retrieval and context systems powering AI workflows - Build and scale graph-based infrastructure and semantic retrieval systems - Improve observability, debugging, and reliability across distributed agent systems - Work on real-time data ingestion and streaming architectures - Collaborate closely with platform, AI, and product engineering teams - Help shape the long-term architecture behind Rox’s agent runtime PROBLEMS YOU’LL WORK ON - Reliability for long-horizon AI workflows - Agent orchestration across distributed systems - Deterministic execution for autonomous systems - Streaming context ingestion and retrieval - Knowledge graph infrastructure - Real-time state synchronization - Low-latency execution pipelines - Enterprise-grade observability for agent systems MUST-HAVE QUALIFICATIONS - Strong background in distributed systems or platform engineering - Experience building and operating high-scale backend infrastructure - Strong systems fundamentals across networking, concurrency, storage, and reliability - Experience with streaming systems, distributed databases, or real-time infrastructure - Ability to independently design and ship complex technical systems - Strong product and engineering judgment PARTICULARLY RELEVANT BACKGROUNDS We’d especially love to speak with engineers who have experience in areas like: - Apache Flink - distributed query engines - real-time OLAP systems - graph retrieval systems - semantic search infrastructure - streaming compute systems - large-scale platform engineering - AI infrastructure and orchestration systems Open source contributors, infrastructure specialists, and engineers who have historically operated as technical force multipliers inside their organizations tend to thrive here. WHAT SUCCESS LOOKS LIKE IN YOUR FIRST FEW WEEKS You understand Rox’s architecture, agent runtime, and infrastructure stack deeply enough to contribute to production systems. IN YOUR FIRST FEW MONTHS You are independently designing and improving core systems tied to agent reliability, execution, and retrieval performance. OVER TIME You help define the technical foundation that enables autonomous enterprise workflows to operate reliably at massive scale. WHY THIS ROLE EXISTS Enterprise AI systems are moving toward autonomous execution. The hard problem is not generating outputs — it’s building reliable systems that can reason, retrieve context, coordinate actions, and operate deterministically under real-world enterprise constraints. We believe this requires a new category of infrastructure engineering. That is the problem space this team exists to solve. LOCATION This role is based onsite in San Francisco. We strongly believe that the speed and complexity of the problems we are solving benefit from in-person collaboration. We actively relocate exceptional engineers from around the world and currently have team members who have moved from Europe, Canada, Asia, and Australia to join Rox. If you want to work on deep infrastructure problems at the frontier of autonomous systems, we’d love to talk.