AI QA Engineer

SIRO Clinpharm Pvt. Ltd.

United States

Remote

USD 120,000 - 180,000

Full time

11 days ago

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Job summary

SIRO Clinpharm Pvt. Ltd. is seeking an experienced AI/ML Quality Engineer to ensure quality, reliability, and compliance of AI/ML, GenAI, LLMs in pharma/manufacturing environments.

The ideal candidate will have expertise in model evaluation, GenAI testing, automated QA pipelines, and AI risk assessment. Regulated environments preferred.

Qualifications

  • 5+ years of experience in AI/ML quality engineering
  • Experience with GenAI testing, LLM evaluations
  • Experience in regulated or quality-critical environments preferred
  • Strong Python, APIs, scripting, and automation skills

Responsibilities

  • Develop and execute AI/ML model QA strategies across the model lifecycle
  • Evaluate models using Accuracy, Precision, Recall, F1, ROC/AUC, Confusion Matrix
  • Test GenAI and LLM evaluations for accuracy, relevance, and hallucinations
  • Design testing for AI agents and multi-agent workflows, including tool calling and output validation

Skills

Python
APIs
Scripting
Automation
LangChain
LangGraph
Langfuse

Tools

Python
APIs
Scripting
Automation frameworks
LangChain
LangGraph
Langfuse

Job description

Greetings !
We are hiring for TCS Client!
Role : AI/ML & GenAI Quality Engineer
Experience: 5+ Years
Work Mode: Remote
Role: AI/ML Model QA / GenAI Validation Engineer
Job Summary

We are looking for an experienced AI/ML & GenAI Quality Engineer to ensure the quality, reliability, performance, and compliance of AI/ML, Generative AI, Large Language Models (LLMs), and Agentic AI solutions within a pharmaceutical and manufacturing environment.

The ideal candidate will have strong expertise in AI/ML model evaluation, GenAI testing, automated quality engineering, and AI risk assessment. Experience in regulated or quality-critical environments is preferred.

Key Responsibilities
  • Develop and execute AI/ML model quality assurance and evaluation strategies across the model lifecycle.
  • Evaluate machine learning models using Accuracy, Precision, Recall, F1 Score, ROC/AUC, Confusion Matrix, and other relevant metrics.
  • Test models across diverse datasets, edge cases, failure scenarios, and operating conditions.
  • Perform GenAI and LLM evaluations for accuracy, relevance, consistency, hallucination, groundedness, and response quality.
  • Design and execute testing strategies for AI agents and multi-agent workflows, including orchestration, tool calling, and output validation.
  • Build test datasets, evaluation frameworks, test harnesses, and automated QA pipelines.
  • Use Python, APIs, scripting, and automation frameworks for AI testing and evaluation.
  • Work with LangChain, LangGraph, Langfuse, and similar tools for agent development, tracing, observability, and evaluation.
  • Identify model bias, data drift, hallucinations, instability, and AI application failures, and perform root-cause analysis.
  • Define test cases, user stories, acceptance criteria, quality thresholds, and production-readiness criteria.
  • Collaborate with Data Scientists, ML Engineers, Software Engineers, Product Owners, and business stakeholders.
  • Document test results, model limitations, risks, defects, and evaluation outcomes in an audit-ready format.
  • Support Responsible AI, AI Governance, Data Integrity, and Quality-by-Design practices.
  • Conduct AI Red-Teaming and adversarial testing to identify vulnerabilities, unsafe outputs, and potential failure modes.
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