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トレンド企業

トレンド企業

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求人Amgen

IT Quality- QA AI Specialist

Amgen

IT Quality- QA AI Specialist

Amgen

India - Hyderabad

·

On-site

·

Full-time

·

1w ago

Career Category

Quality

Job Description Position Summary / Purpose

This role is accountable for the end-to-end global process that ensures AI-enabled systems used in GxP contexts are validated/qualified and maintained in a state of control throughout their lifecycle, consistent with the company’s Quality Management System (QMS) expectations for global process ownership and controlled document architecture.

This role is validation/qualification-specific and operates in partnership with the existing global Business Process Owner (BPO) for Responsible Use of AI for GxP, who owns overarching responsible-use governance and user controls (e.g., human-in-the-loop expectations and usage constraints) and good understanding on the Global AI Regulatory requirements (EU Act, FDA).

Scope

Applies to AI systems, models, and tools (standalone or embedded) used to generate information or data supporting GxP-regulated activities, including the validation pathway that incorporates AI trustworthiness/credibility assessment and the associated templates and controlled records.

Key Responsibilities (Accountabilities)

  1. Contributed and supports global AI validation/qualification process (end-to-end)
  • Maintain a compliant global quality process for AI validation/qualification and ensure alignment with QMS architecture and global documentation expectations.
  • Define and maintain the global procedural framework for validating AI-enabled GxP systems, including integration points with system validation/SDLC expectations and responsible-use controls.
  • Ensure the process is risk-based and scaled to AI context of use and impact, with clear decision gates and required evidence expectations.
  • Robust understanding on the LLM and Machine development life cycle approaches.
  • Able to support in shifts based on the project needs in EST, PST Timezone.
  1. Own and maintain controlled documentation, templates, and required records
  • Own/maintain the core global procedures and templates supporting AI validation/qualification, including credibility/trustworthiness assessment documentation and controlled report formats.
  • Ensure documents are periodically reviewed and revised consistent with QMS role expectations for global process ownership.
  1. Governance integration & cross-functional alignment
  • Partner with the Responsible Use BPO and governance stakeholders to ensure validation/qualification requirements align with responsible-use constraints (e.g., independent human verification and traceability expectations).
  • Coordinate with QA, Business Owners, System SMEs/IT Application Owners, and AI Model SMEs to ensure validation deliverables reflect business, compliance, and IS requirements and are stored in appropriate controlled repositories.
  1. Enable global deployment through training and guidance
  • Provide execution guidance, coaching, and job aids to sites/functions on implementing the global AI validation/qualification process locally while maintaining global consistency.
  • Contribute to training curricula and support communities of practice to build consistent capability across the network.
  1. Continuous improvement, metrics, and inspection readiness
  • Define and communicate process performance metrics and drive continuous improvement opportunities.
  • Support inspection readiness by ensuring validation evidence expectations are clear, auditable, and consistently applied.

Decision Rights / Authority

  • Process authority for the global AI validation/qualification procedure, templates, and required records.
  • Authority to set minimum global validation expectations and recommend/drive harmonization decisions through established governance.

Key Interfaces (Stakeholders)

  • Global BPO – Responsible Use of AI in GxP
  • Quality Assurance (GxP computerized systems validation)
  • Business Owners, System SMEs / IT Application Owners
  • AI Model SMEs (data science/statistical credibility)
  • Cross-functional governance stakeholders (e.g., privacy, cybersecurity, sourcing, architecture) as applicable

Required Qualifications

Education:

  • Master’s degree with a minimum of 10 years experience in Software and Systems Quality assurance OR
  • Bachelor’s degree with a minimum of 12 years of Software and Systems Quality assurance experience

Experience:

  • Demonstrated experience in GxP computerized systems validation/qualification and lifecycle management.
  • Experience developing, maintaining, and deploying controlled documents and templates within a regulated QMS environment.
  • Familiarity with AI governance expectations in GxP contexts, including responsible-use constraints such as human oversight and independent verification.
  • Working knowledge of AI trustworthiness/credibility assessment concepts and documentation practices used to support validation decisions.

Skills / Competencies:

  • Strong process orientation and document quality discipline (controlled documentation, traceability, clarity).
  • Ability to influence without authority across global, cross-functional stakeholders.
  • Risk-based thinking and ability to translate policy/standards into practical, scalable validation deliverables.
  • Clear written and verbal communication; training and coaching capability.

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Amgenについて

Amgen

Amgen

Public

A biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases.

10,001+

従業員数

Thousand Oaks

本社所在地

$138B

企業価値

レビュー

3.6

10件のレビュー

ワークライフバランス

3.2

報酬

4.1

企業文化

3.4

キャリア

2.8

経営陣

3.5

65%

友人に勧める

良い点

Excellent benefits and health benefits

Good pay and compensation

Supportive management and strong leadership

改善点

Limited career growth and promotion opportunities

Work-life balance challenges and long hours

Bureaucratic processes

給与レンジ

1,244件のデータ

L2

L3

L4

L5

L6

L2 · Financial Analyst L2

0件のレポート

$94,068

年収総額

基本給

$37,627

ストック

$47,034

ボーナス

$9,407

$65,848

$122,288

面接体験

5件の面接

難易度

3.0

/ 5

期間

14-28週間

内定率

40%

体験

ポジティブ 20%

普通 80%

ネガティブ 0%

面接プロセス

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Role-Specific Interview

5

Panel Interview

6

Offer

よくある質問

Technical Knowledge

Behavioral/STAR

Past Experience

Data Analysis/Statistics

Culture Fit