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Salary
≈ $9.5k – $25k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp

First seen by Alion on Aug 31, 2026.

Overview
Company
Impact
Profile match
TruEra provides AI-based solutions to help enterprises analyze machine learning, improve model quality, faster deployment, and build trust by addressing unfair bias and ensuring governance and compliance.

Responsibilities:

  • Design and build end-to-end test infrastructure for zaimler's backend services, APIs, and data pipelines.
  • Own performance and load testing: define benchmarks, build harnesses, and establish baselines for latency, throughput, and resource consumption under production-realistic conditions.
  • Build and maintain integration test suites that validate correctness across the full stack, from data ingestion through knowledge graph construction to inference endpoints.
  • Develop automated regression and smoke test pipelines integrated into CI/CD, ensuring every deploy is validated before it reaches enterprise customers.
  • Identify reliability risks early by instrumenting systems, analyzing failure modes, and building chaos/fault-injection tests for critical paths.
  • Collaborate directly with infrastructure and ML engineers to define testability requirements for new systems before they're built, not after.

Requirements:

  • 4+ years of experience in software engineering, test engineering, or a related role.
  • Strong software engineering fundamentals: you write production-grade code, not just test scripts.
  • Deep experience with backend and API testing: REST/gRPC, async workflows, distributed systems.
  • Hands-on experience building performance and load testing frameworks (e. g., Locust, k6 Gatling, or custom tooling).
  • Proficiency in Python; familiarity with Go or Java is a plus.
  • Experience with CI/CD pipelines (GitHub Actions, Jenkins, or similar) and containerized environments (Docker, Kubernetes).
  • Understanding of data pipeline testing, validating correctness, consistency, and completeness across ETL or streaming systems.

Nice-to-haves:

  • Experience testing graph databases, knowledge graphs, or semantic/ML inference systems.
  • Familiarity with observability tooling (Prometheus, Grafana, Datadog) and using metrics to drive test strategy.
  • Background in infrastructure-as-code and environment provisioning for test environments.
  • Experience at a startup or early-stage company where you built testing practices from scratch.
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