AI/ML Engineer with Regulatory data

Key Responsibilities

1. Collaboration & Design:

   • Work with product teams, technology services, and architects to design scalable and supportable systems aligned with regulatory strategies.
   • Create architecture artifacts such as business context diagrams, process overviews, data flow diagrams, application/data/integration/infrastructure architectures, and ML Ops architectures.

2. Strategy Alignment:

   • Align solutions with regulatory, enterprise, and R&D technology strategies, patterns, and standards.
   • Simplify the application landscape through integration and intelligent automation.

3. Tool Utilization:

   • Document architecture and design using tools like Lean IX, SAXpress, Draw-IO, Confluence, MS Teams, etc.

4. Product Roadmap Support:

   • Ensure roadmaps align with regulatory strategies, architectural principles, and enterprise requirements for ALM/TLM.

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Qualifications

<>Education

• Required: BA/BS in technical, engineering, or scientific fields.
• Certifications:
  • AWS-Certified Solutions Architect (Required).
  • AWS Well-Architected Framework (Desirable).
  • AWS Certified Machine Learning Specialty (Desirable).

<>Experience & Skills

1. Domain Knowledge:

   • Regulatory data and content in pharmaceutical development.
   • Experience architecting regulated systems (GxP, HPIAA, GDPR).

2. Technical Expertise:

   • Integration design and operationalization (e.g., REST APIs, Kafka, ETL, data pipelines, API gateways).
   • RDBMS and content management platforms.
   • AWS compute, networking, storage, database, machine learning services, and deployment.

3. Digital Automation:

   • 2 3 years in BPM, RPA, NLP, and ML-based solutions.

4. Leadership & Communication:

   • Lead workshops, resolve ambiguity, and build consensus.
   • Proven ability to articulate business requirements and IT roadmaps.

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