AI Architect

5+ years of experience in healthcare AI, with a strong understanding of workflows, medical terminologies, and healthcare interoperability standards

Proven ability to design AI systems that support decision-making, predictive analytics, health management, etc

Technical Proficiency:

13+ years in software engineering, data science, or AI, with 5+ years in AI/ML architecture roles.

Expertise in machine learning, deep learning, natural language processing (NLP), and computer vision applied to healthcare.

Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.

Experience with cloud platforms (AWS, Azure) and MLOps tools (MLflow, SageMaker).

Strong understanding of data engineering pipelines, ETL processes, and real-time data streaming

Architectural & Strategic Experience:

Demonstrated success in designing scalable, secure, and high-availability AI architectures in healthcare settings.

Experience with model lifecycle management, including monitoring, retraining, and drift detection in clinical environments.

Ability to assess and mitigate bias, fairness, and explainability issues in AI models.

Familiarity with enterprise architecture frameworks and AI governance models.

Preferred Behavioral Skills

Highly motivated/self-starter with a sense of ownership, willingness to learn, and desire to succeed

Strong teamwork, problem-solving, and analytical skills

Strong understanding of Pharma Quality Standards and Practices

Proven leadership in cross-functional teams, including business teams, data scientists, and IT professionals.

Strong communication skills to convey complex AI concepts to non-technical stakeholders, including healthcare executives and regulatory bodies.

Experience in strategic planning, vendor evaluation, and AI capability building within healthcare organizations