
11 - 50 Mitarbeiter
Gegründet 2021
💼 Beratung
👥 HR Tech
☁️ SaaS
Consulting • HR Tech • SaaS
Weekday ist eine moderne Rekrutierungsplattform, die KI-Technologien mit einer umfangreichen Datenbank potenzieller Kandidaten kombiniert, um den Einstellungsprozess für Unternehmen in Indien zu optimieren. Sie bieten verschiedene Dienstleistungen an, einschließlich eines proaktiven Outreach-Ansatzes, der Arbeitgebern hilft, mit Top-Talenten in Kontakt zu treten, sowie Tools für Kandidaten, um sich einfach auf Stellen zu bewerben. Weekdays Schwerpunkt auf Kandidatenbindung über mehrere Kanäle, einschließlich E-Mail, WhatsApp und Telefonanrufen, hebt sie im wettbewerbsintensiven Marktumfeld der Personalagenturen ab.
🕒 vor 11 Tagen
🗣️🇺🇸🇬🇧 Englisch erforderlich
AWS
Azure
Cassandra
DynamoDB
Google Cloud Platform
HBase
Java
JavaScript
Jenkins
Kubernetes
MongoDB
Node.js
NoSQL
Python
Redis
Rust
Thrift
C++
Go
.NET
Woher diese Stelle stammt
Veröffentlicht auf der Karriereseite von Weekday (YC W21) ↗, nicht über eine Jobbörse
Von Remote Rocketship zum ersten Mal gesehen vor 11 Tagen
Noch offen auf der Website von Weekday (YC W21). Geprüft vor 15 Stunden.

11 - 50 Mitarbeiter
Gegründet 2021
💼 Beratung
👥 HR Tech
☁️ SaaS
Consulting • HR Tech • SaaS
Weekday ist eine moderne Rekrutierungsplattform, die KI-Technologien mit einer umfangreichen Datenbank potenzieller Kandidaten kombiniert, um den Einstellungsprozess für Unternehmen in Indien zu optimieren. Sie bieten verschiedene Dienstleistungen an, einschließlich eines proaktiven Outreach-Ansatzes, der Arbeitgebern hilft, mit Top-Talenten in Kontakt zu treten, sowie Tools für Kandidaten, um sich einfach auf Stellen zu bewerben. Weekdays Schwerpunkt auf Kandidatenbindung über mehrere Kanäle, einschließlich E-Mail, WhatsApp und Telefonanrufen, hebt sie im wettbewerbsintensiven Marktumfeld der Personalagenturen ab.
• Define and drive the overall quality strategy for a distributed database platform • Own test architecture, coverage models, release gates, and risk-based prioritization • Drive quality across server components, client SDKs, operator and backup tooling, and management interfaces • Design testing strategies for replication, rebalancing, partitioning, sharding, consistency, transactions, indexes, query planning, compaction, backup and restore, snapshots, and cross-datacenter replication • Validate cluster correctness under node failures, network partitions, clock skew, disk-full scenarios, slow disks, rolling upgrades, mixed-version deployments, and long-running soak tests • Design and execute fault-injection scenarios and investigate complex system defects • Reproduce defects at source-code level and provide minimal reproducible test cases and root-cause analysis • Build and maintain scalable Python/pytest test frameworks, custom harnesses, API testing, and end-to-end automation • Ensure test suites run reliably in shared infrastructure and CI/CD environments including GitHub Actions and Jenkins • Reduce flaky tests, identify noisy failures, and strengthen regression coverage • Lead integration of AI agents into testing frameworks for test generation, failure triage, and agent-reliability evaluation • Design agent workflows to execute tests, inspect logs, traces, metrics, and database state, and generate defect reports • Develop evaluation frameworks using golden datasets, graders, and regression suites • Participate in feature reviews, requirements discussions, design reviews, and client specifications to define testability requirements • Create test plans, collaborate with development teams, and convert incidents into regression tests and monitoring checks • Drive defect resolution across QE, client, and server engineering teams • Mentor senior QEs and SDETs and establish quality standards without direct people-management responsibilities
• 10–18 years of experience in Software Quality Engineering, SDET, or Systems Engineering, with strong focus on quality systems and demonstrated Staff or Principal-level technical impact • Deep hands-on experience testing distributed databases or storage systems, preferably NoSQL platforms such as Cassandra, ScyllaDB, MongoDB, Couchbase, Redis, DynamoDB, or HBase; distributed relational database experience also relevant • Strong experience testing replication, partitioning, sharding, consistency, transactions, secondary indexes, backup and restore, and cross-datacenter replication • Solid understanding of distributed-systems fundamentals, including replication protocols, consensus, quorum reads and writes, strong and eventual consistency, split-brain scenarios, clock skew, and failure/recovery semantics • Ability to read and debug server-side code written in C, C++, Go, Rust, or Java and trace defects to specific functions and root causes • Understanding of protocol and serialization edge cases, including wire formats, MessagePack, Protocol Buffers, Thrift, and compression codecs • Strong software engineering and automation skills in Python, with proficiency in at least one systems programming language • Practical experience with fault injection, GDB, chaos-style testing, process termination, network partitions, latency and packet-loss injection, disk faults, corrupted inputs, version skew, and boundary-value testing • Experience across unit, integration, API, contract, end-to-end, performance, scalability, upgrade/downgrade, and soak testing • Proven ability to lead debugging and root-cause investigations across QE, client, and server teams • Strong CI/CD experience with GitHub Actions, Jenkins, or equivalent tools, and shared test infrastructure • Practical experience using AI agents for testing, including agent workflows, tool integration, prompt and evaluation design, and real-world testing framework integration • Excellent written and verbal communication skills • Preferred: client SDK testing across Python, Java, Go, C, Node.js, and .NET • Preferred: compatibility matrices, upgrade/downgrade scenarios, and behavioral consistency across client SDKs • Preferred: backup and restore, checkpointing, snapshotting, and WAL/journal correctness at terabyte scale • Preferred: query-engine and secondary-index testing • Preferred: Kubernetes and database operator testing using KUTTL, Chainsaw, or envtest • Preferred: AWS, GCP, or Azure infrastructure, TLS/mTLS, IAM, secrets management, and air-gapped installations • Preferred: security testing, fuzzing, CVE reproduction, and memory-safety issue identification
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