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Senior AI Quality Assurance (QA) Engineer

DATAMAXIS

Bengaluru, Karnataka, IndiaJobNo compensation foundTracked 3w agoSeen in employer's feed 1w ago

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At a glance

Compensation
No compensation found
Location
Bengaluru, Karnataka, India
Work Authorization
Not specified

Job overview

DATAMAXIS is hiring a Senior AI Quality Assurance (QA) Engineer. DATAMAXIS seeks a Senior AI Quality Assurance Engineer in Bengaluru to lead testing of LLM‑powered applications and AI workflows, develop benchmark datasets, and build automated test frameworks using Python and Pytest while ensuring robust API and SQL validation.

Key focus areas include Evaluate LLM‑powered applications and conversational AI systems, Create benchmark datasets for regression testing of AI workflows, and Develop automated tests using Python and Pytest.

Important skills include Evaluating LLM-Powered Applications, Conversational AI Systems, NL2SQL Solutions, AI Workflows, AI Benchmarking Methodologies, and Creating Benchmark Datasets.

Skills & qualifications

RequiredNice to have

Skills

Evaluating LLM-Powered ApplicationsConversational AI SystemsNL2SQL SolutionsAI WorkflowsAI Benchmarking MethodologiesCreating Benchmark DatasetsLang SmithMLflowArize PhoenixAI Evaluation MetricsPrecisionRecallF1 ScoreExact Match (EM)Mean Reciprocal Rank (MRR)Execution AccuracyLatency AnalysisToken Usage AnalysisCost AnalysisPythonPytestUnit TestingIntegration TestingAPI TestingException HandlingMockingFixturesParameterized TestingTesting REST APIsTesting Distributed Backend ServicesSQLValidating Generated QueriesValidating Execution ResultsValidating Schema AlignmentValidating Business LogicAnalytical SkillsDebugging SkillsRoot Cause Analysis

Qualifications

7+ Years Software Quality Assurance Experience7+ Years Test Automation Experience7+ Years AI Quality Engineering Experience

Full job description

Job Position: Senior AI Quality Assurance (QA) Engineer

Experience: 7+ Years  

Location: Bengaluru

Required Skills

  • 7+ years of experience in Software Quality Assurance, Test Automation, or AI Quality Engineering.

  • Hands-on experience evaluating LLM-powered applications, conversational AI systems, NL2SQL solutions, or similar AI workflows.

  • Strong understanding of AI benchmarking methodologies and experience creating benchmark (golden) datasets for regression testing.

  • Experience with AI evaluation and observability platforms such as Lang Smith, MLflow, Arize Phoenix, or equivalent.

  • Strong understanding of AI evaluation metrics, including Precision, Recall, Precision@K, Recall@K, F1 Score, Exact Match (EM), Mean Reciprocal Rank (MRR), Execution Accuracy, latency (P50/P95/P99), token usage, and cost analysis.

  • Strong proficiency in Python with hands-on experience building automation using Pytest, including unit testing, integration testing, API testing, exception handling, mocking, fixtures, and parameterized testing.

  • Experience testing REST APIs and distributed backend services.

  • Strong SQL skills with the ability to validate generated queries, execution results, schema alignment, and business logic.

  • Strong analytical and debugging skills with the ability to perform root cause analysis across complex AI systems.

You've read the whole posting — now see how you match it.