Teams at Nexla

Own reliability for Nexla’s large-scale data plane, including Kafka, Spark, Flink, Ray, Redis, EKS, and GKE. Define data-aware SLOs, error budgets, instrumentation, and reliability standards. Operate stateful distributed systems, lead incident response and postmortems, and automate toil through Python, Terraform, and tooling. Improve failure recovery, capacity, upgrades, and private or air-gapped deployments while influencing engineering teams beyond SRE. This is a hands-on senior role with leadership responsibilities and occasional weekend deployments.

Lead product execution for an AI-native enterprise data integration platform. Responsibilities include researching customer problems, validating market opportunities, prototyping workflows and AI interactions, translating product vision into execution, coordinating engineering and cross-functional teams, synthesizing product signals, and managing releases. The role requires technical fluency in APIs, integrations, distributed systems, data infrastructure, developer platforms, and AI workflows, along with strong customer empathy and comfort operating in ambiguity.

Build and operate backend JVM services, SDKs, streaming runtimes, and distributed data-processing systems. Responsibilities include designing framework features, supporting Kafka, Spark, and Flink workloads, managing concurrency and latency, debugging production failures, and developing reliability guardrails. The role requires ownership from design through deployment and on-call, with significant work in Java, distributed systems, data integration, and production operations.