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Artificial Intelligence Engineer

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Remote

Artificial Intelligence Engineer

Siro Clinpharm

Artificial Intelligence Engineer

Skills

Google Cloud PlatformPythonData ScienceTesting & QAMachine LearningAIAWSComplianceAzure

13 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Remote

Published on:

9 October 2026

What they need


AI QA Engineer/Consultant

Remote

Experience:

5+ years in AI/ML, GenAI, Model QA/Validation, Software QA, Data Science, or Quality Engineering, preferably with experience in regulated or quality-critical environments.

Role Overview: Responsible for ensuring the quality, reliability, performance, and compliance of AI/ML, GenAI, LLM, and Agentic AI solutions within Pfizers pharmaceutical and manufacturing environment**.**

Key Responsibilities

  • Develop and execute AI/ML model QA and evaluation strategies across the model lifecycle.
  • Evaluate ML models using Accuracy, Precision, Recall, F1, ROC/AUC, Confusion Matrix, and other relevant metrics.
  • Test models across datasets, edge cases, failure scenarios, and different operating conditions.
  • Perform GenAI/LLM evaluation for accuracy, relevance, consistency, hallucination, groundedness, and response quality.
  • Design and execute testing 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 for AI testing and evaluation.
  • Work with LangChain, LangGraph, Langfuse and similar tools for agent development, tracing, observability, and evaluation.
  • Identify bias, drift, hallucination, instability, and model/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.

Must-Have Skills

  • Machine Learning & Model Evaluation
  • GenAI / LLM Evaluation
  • Agentic AI & Multi-Agent Systems
  • Precision, Recall, F1, ROC/AUC, Confusion Matrix
  • Test Strategy & Test Case Design
  • Python, APIs & Automation
  • LangChain, LangGraph, Langfuse
  • Prompt Engineering & LLM Testing
  • AI Risk, Bias & Robustness Testing
  • Model/AI Application Regression Testing
  • Strong Analytical & Stakeholder Management Skills

Good to Have

  • Pharmaceutical / Life Sciences experience
  • GxP / CSV / Data Integrity knowledge
  • Azure / AWS / GCP
  • MLOps / LLMOps / ModelOps
  • RAG & Vector Databases
  • Responsible AI & AI Governance
  • CI/CD and automated testing
  • AI Red-Teaming / Adversarial Testing

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