Actively Hiring

Senior Data & AI Quality Engineer - Chennai (Hybrid)

Location

Chennai, Tamil Nadu

Work Mode

On-site, Hybrid

Experience

5-10 Yrs

Salary Range

INR 20-25 LPA

Job Type

Permanent

Openings

1 position

Job Description

Hiring for: A US-based, AI-first data solutions company founded by seasoned technology leaders.

Role: Senior Data & AI Quality Engineer - Chennai (Hybrid)

Positions: 1

Experience: 5 to 10 years

Location(s): Chennai

Type: On-site, Hybrid / Permanent

Salary: Up to INR 25 LPA (best as per the fitment)

Notice Period: Immediate to 30 days


Key Responsibilities:

• Ingestion pipelines: Confluence, SharePoint/Microsoft 365 (Graph), and repository connectors - parsing, chunking, metadata, incremental sync, data-quality controls

• Synthetic and non-production data design: corpora shaped to banking IT content (runbooks, incidents, KB articles, change records) with realistic permission structures the foundation of the cloud-first build

• The evaluation harness as a product: golden question sets, retrieval precision/faithfulness/citation-accuracy scoring, the zero-leakage permission suite, the zero-unauthorized-actions agent suite; CI-integrated regression gates

• Performance and load testing with the platform engineer: concurrency profiles, soak tests, degraded-mode behavior

• UAT orchestration and defect triage across both use cases; acceptance evidence packs per milestone

• Measurement reporting foundations: the before/after value metrics (time saved per incident, per search) the client's executives receive monthly


Technical Skills:

• 5+ years across data engineering and quality engineering with production Python; you have built pipelines AND the tests that police them

• LLM evaluation experience: has designed or operated retrieval/generation quality measurement with numeric thresholds (RAGAS-class metrics, custom harnesses, or equivalent) not just eyeballed outputs

• Document-processing depth: parsing real enterprise content (tables, permissions, versions, mess), chunking trade-offs, metadata design

• Test-suite craftsmanship: negative and adversarial test design the leakage suite is a security artifact, and you think like an attacker when writing it

• Load/performance testing experience (Locust, k6, or equivalent) and defect-triage discipline

Screening Questions

Please note that you will be asked to answer these questions during the application process:

  • 1.How many years of experience do you have with Python?
  • 2.Current location
  • 3.Current CTC (Lakhs per annum)
  • 4.Expected CTC (Lakhs per annum)
  • 5.Notice period
  • 6.Are you currently serving notice period?
  • 7.Have you worked on data ingestion pipelines and automated data validation/testing in production?
  • 8.Have you tested or evaluated RAG/LLM applications?
  • 9.Have you used RAGAS or built a custom framework to measure AI response quality?
  • 10.Have you worked with document processing, chunking, embeddings, or vector search?
  • 11.Have you performed negative/security testing to check whether an AI system exposes information a user isn't authorized to access?

Skills & Technologies

Required Skills
Adversarial TestingData PipelinesData QualityData Quality TestingDocument ProcessingEvaluation FrameworksLLMLoad TestingMilvusPerformance TestingPgVectorPythonQuality EngineeringRAG EvaluationRAGASRegulated Environment ComplianceRetrieval Accuracy MetricsSecurity TestingSharePoint, Microsoft Graph API, and Confluence IntegrationsSynthetic Data GenerationTest Automation
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