Staff Engineer – Distributed Systems

. Design, build, and scale backend systems and frontend interfaces powering the Threads & Composer experience inside HighLevel Conversations .

Posted 9/25/2026full-timeRemote • IndiaLeadWebsite

Tools & technologies

CloudDistributed SystemsElasticSearchGoogle Cloud PlatformJavaScriptKubernetesMongoDBNode.jsNoSQLRedisSQLTypeScriptVue.jsGo

Key responsibilities & impact

Design, build, and scale backend systems and frontend interfaces powering the Threads & Composer experience inside HighLevel Conversations
Own backend and API design, data flows, performance, reliability, throughput, and correctness at scale
Own the Vue 3 UI layer end-to-end
Maintain architecture health of a billion-scale distributed system, including failure modes, capacity limits, consistency guarantees, and interactions across 50+ deployments
Approve critical-path designs and make architecture decisions across teams
Proactively identify and fix single points of failure, unbounded queues, missing idempotency, thundering herds, and data-loss windows
Prototype risky architectural changes, remediate serious incidents, and pair on complex cross-team bugs
Build resilience through degradation strategies, backpressure, isolation boundaries, and capacity models supporting 10%+ month-over-month growth
Raise engineering standards through design reviews, post-mortems, and reusable patterns
Establish safe AI-assisted engineering practices for critical systems
Work with Node.js/TypeScript, Go, GKE, GCP Pub/Sub, Cloud Tasks, Redis, MongoDB, Firestore, ClickHouse, and Elasticsearch
Improve Workflows critical paths through ownership, capacity models, tested failure modes, and incident reduction

What you’ll need

10+ years of engineering experience with deep, hands-on ownership of large-scale distributed systems
Sole accountability for a production system through real failures
Deep command of queueing and asynchronous architectures, delivery semantics, ordering, backpressure, idempotency, exactly-once and at-least-once delivery
Strong knowledge of multiple SQL and NoSQL storage engines, consistency models, and indexing at scale
Expert-level depth in Redis or comparable in-memory systems, including failure modes under memory pressure and network partitions
Production experience with Kubernetes at scale, including resource limits, autoscaling behavior, and node-pool failures
Exceptional design communication through documentation, diagrams, and root-cause analyses
Fluency in Node.js and/or Go sufficient to prototype proposals and ship critical-path fixes
Comparable large-scale experience with hundreds of services or thousands of instances and billions of daily events strongly preferred
Experience with AI agents, GCP-native services, taking 0→1 systems to production, and hardening mature systems listed as bonus points

Comp & perks

Global, remote-first organization
Equal Opportunity Employer
Voluntary demographic information process; information kept separate from application and not used in hiring decision
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