Sr Automation QA (JS) Engineer

Job highlights

• Design,build,and maintain automated test suites for the platform,Frontend and Backend,including contract tests that protect the agent-developer experience as the SDK evolves .
• Temporal or a similar workflow engine a strong plus . Strong CI / CD integration skills (GitHub Actions or equivalent) and the discipline to design release gates .
• Experience with qTest for test management

Job Summary

Ciklum is looking for a Senior Automation QA (JS) Engineer to join our team full-time in India.

As a Senior Automation QA (JS) Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

Responsibilities

• Design, build, and maintain automated test suites for the platform, Frontend and Backend, including contract tests that protect the agent-developer experience as the SDK evolves

• Build automated tests for long-running Temporal workflows including failure injection (worker kill, provider outage, retry storms) to verify durable-execution guarantees such as zero lost runs and correct compensation/saga behavior

• Automate multi-tenant isolation verification cross-tenant data access, configuration bleed, and cost-attribution correctness executed per release as a platform acceptance criterion

• Verify agent execution sandboxing and egress controls through negative testing of disallowed tool calls and network destinations

• Design test strategies for LLM-driven behavior: statistical assertions over repeated runs (pass^k consistency), semantic-similarity scoring, confidence-threshold validation, and flakiness quarantine that distinguishes model variance from genuine regression

• Build and continuously extend adversarial test corpora document-borne prompt injection in lease PDFs, tool-call hijack, and data-exfiltration probes aligned to OWASP LLM Top 10 and recognized red-team taxonomies

• Verify Human-in-the-Loop (HITL) escalation behavior confidence thresholds fire correctly and no gated/irreversible action completes without authorization

• Partner with the evaluation function on golden-dataset-driven checks, contributing test infrastructure, synthetic-data (synthetic lease) pipelines, and CI integration that make agent quality measurable and repeatable

• Automate verification of platform NFRs invocation overhead (p95), concurrency targets, queue backpressure behavior, and LLM provider failover time and surface trends per release

• Use tracing data (Langfuse / OpenTelemetry spans) as a first-class test asset: assert on trace completeness, token/cost-accounting accuracy, and alerting behavior for anomalous runs

• Wire test suites into CI/CD as hard release gates with automated, per-metric regression flagging on pull requests

• Produce auditable, reproducible test-evidence packs that feed directly into client milestone sign-off

• Embed with AI and platform engineers from the design stage making acceptance criteria, testability, and observability inputs to architecture, not afterthoughts

• Maintain test environments, mocked LLM/provider layers, and synthetic data generators that keep test runs fast, deterministic where possible, and affordable

• Mentor mid-level QA engineers, codify AI testing patterns into reusable internal frameworks, and contribute to Ciklums quality engineering practice and AI Academy

  Requirements

• 8+ years of test automation with API testing, and building test frameworks other engineers adopt, not just test cases

• Hands-on experience testing LLM-powered or other non-deterministic systems statistical assertions, semantic scoring, and managing model variance (this is the differentiator; cite real examples)

• Experience testing asynchronous, event-driven systems failure injection, idempotency verification, eventual-consistency assertions; Temporal or a similar workflow engine a strong plus

• Strong CI/CD integration skills (GitHub Actions or equivalent) and the discipline to design release gates

• Solid SQL and data-validation skills; comfort building synthetic test-data pipelines and measuring dataset quality

• A security-testing and adversarial mindset; familiarity with prompt-injection techniques or a strong AppSec testing background with willingness to specialize fast

• Demonstrated judgment on what "tested enough" means under milestone pressure, and the ability to defend quality evidence to non-engineering stakeholders

• Strong proficiency in Playwright and TypeScript is mandatory for building automated test suites

• QA Automation Core: Extensive experience in building automated test frameworks (Playwright/Typescript-based) and integrating them into high-security CI/CD pipelines

• AI/LLM Literacy: Deep understanding of Large Language Model behaviors, prompt sensitivity, and the common failure modes of RAG (Retrieval-Augmented Generation) systems

• Analytical Mindset: Strong capability in statistical analysis to interpret evaluation scores and provide actionable feedback to AI Engineers for prompt tuning

  Desirable

• Performance/load tooling (k6, Locust) for concurrency and latency NFR verification

• Prior testing of multi-tenant SaaS isolation

• Exposure to eval/observability stacks (Langfuse, LangSmith, Promptfoo, DeepEval, Arize Phoenix)

• Compliance evidence experience (SOC 2, GDPR) or accessibility testing (Section 508 / WCAG)

• Familiarity with Commercial Real Estate workflows (lease accounting, CAM reconciliation) or document-extraction systems (OCR, layout parsing)

• Experience using LLMs to generate test cases, adversarial payloads, or synthetic documents

• Performance Testing: Experience testing high-concurrency background processing within agentic systems

• Experience with qTest for test management

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