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AI Testing Engineer, Amazon Bedrock

Job in Austin, Travis County, Texas, 73301, USA
Listing for: NTT DATA, Europe & LATAM, Branch in USA, Inc.
Full Time position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), IT QA Tester / Automation
Salary/Wage Range or Industry Benchmark: 20 - 25 USD Hourly USD 20.00 25.00 HOUR
Job Description & How to Apply Below

Location:100% remote, seeking candidates located in LATAM.

Contract Length:1 year, with potential for extension.

Contract Rate: $20-25per hour in USD. Final rate will be determined based on relevant experience and overall fit for the position.

NTT DATA is seeking an
AI Testing Engineer, Amazon Bedrock to define and execute the quality strategy for Generative AI applications and AI agents used in Customer Service and Contact Center scenarios. This role will evaluate AI outputs across deterministic and non-deterministic scenarios using automation, semantic and statistical analysis, human review, and adversarial testing while partnering with AI engineers and functional QA teams.

Responsibilities:

  • Define the testing and evaluation strategy for Generative AI applications and AI agents.
  • Create and maintain evaluation datasets, golden datasets, and regression suites covering representative business scenarios.
  • Design single-turn and multi-turn conversational test cases, including context retention and workflow transitions.
  • Evaluate AI outputs for accuracy, relevance, completeness, groundedness, faithfulness, consistency, tone, safety, and compliance.
  • Build automated evaluation pipelines and integrate AI-quality checks into CI/CD and release processes.
  • Detect regressions introduced by changes to prompts, models, knowledge sources, retrieval strategies, tools, or guardrails.
  • Design negative and adversarial test scenarios covering prompt injection, jailbreaks, hallucinations, PII leakage, unsafe responses, and out-of-scope requests.
  • Validate fallback behavior, uncertainty handling, tool execution, error handling, and escalation to human agents.
  • Perform root-cause analysis for incorrect or undesirable AI outputs and collaborate with AI engineers on remediation.
  • Define measurable quality thresholds and release acceptance criteria for AI-agent capabilities.
  • Produce quality metrics, evaluation reports, dashboards, and trend analysis for project and product stakeholders.
  • Support UAT preparation, defect triage, production monitoring, and continuous improvement of AI behavior.

Required Experience:

  • 5+ years of experience in software testing, quality engineering, or test automation with hands-on automation capabilities.
  • 2+ years of experience with Amazon Bedrock.
  • Practical understanding of Generative AI / LLM behavior and the challenges of testing non-deterministic systems.
  • Experience designing test scenarios for conversational applications, chatbots, virtual assistants, or AI agents.
  • Experience testing REST APIs and backend services.
  • Experience working with structured test data in formats such as JSON and CSV.
  • Understanding of evaluation concepts such as groundedness, faithfulness, relevance, hallucination detection, semantic similarity, and human evaluation.
  • Experience with Git, CI/CD, automated regression testing, and defect-management workflows.
  • Strong analytical skills and ability to investigate why an AI output failed rather than only identifying that it failed.
  • Professional proficiency in English.

Nice-to-Have:

  • Experience with AI evaluation frameworks such as RAGAS, Deep Eval, Promptfoo, Lang Smith, Tru Lens, or equivalent tools.
  • Experience evaluating RAG systems, retrieval quality, or enterprise knowledge assistants.
  • Experience with Amazon Bedrock and AWS services.
  • Experience testing Amazon Connect, Contact Center, agent-assist, or Customer Service applications.

Education &

Certifications:

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field.

Required Equipment: This role requires the use of a personal laptop. Candidates must be comfortable with company security software and device management tools being installed on their laptop as…

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