Dir. Ddit Dev. Data, Analyt, Ds&ai

**Summary**:
**About the Role**:
**Key Responsibilities**
- ** GenAI Strategy & Roadmap**: Define and implement a generative AI architecture and roadmap aligned with business goals in pharma and life sciences.
- ** Solution Design**: Architect scalable GenAI solutions for drug discovery, medical writing automation, clinical trials, regulatory submissions, and real-world evidence generation.
- ** Cloud & On-Prem AI Infrastructure**: Design GenAI solutions leveraging cloud platforms (AWS, Azure, GCP) or on-premise infrastructure while ensuring data security and regulatory compliance.
- ** MLOps & Deployment**: Implement best practices for GenAI model deployment, monitoring, and lifecycle management within **GxP-compliant** environments.
- ** Compliance & Governance**: Ensure GenAI solutions comply with **regulatory standards (FDA, EMA, GDPR, HIPAA, GxP, 21 CFR Part 11)** and adhere to responsible AI principles, including bias mitigation and explainability.
- ** Performance Optimization**: Drive efficiency in generative AI models, ensuring cost optimization and scalability while maintaining data integrity and compliance.
- ** Stakeholder Collaboration**: Work with cross-functional teams, including platform teams, and Drug Development teams, to align GenAI initiatives with enterprise and industry-specific requirements.
- ** Research & Innovation**: Stay updated with the latest advancements in **GenAI, multimodal AI, AI agents, and synthetic data generation** to incorporate emerging technologies into the company’s AI strategy.

**Required Qualifications**
- Bachelor's or Master's degree in Computer Science, AI, Data Science, Bioinformatics, or a related field.
- ** Experience**: 8+ years in AI/ML development with at least 2 years in an AI Architect or GenAI Architect role in pharma, biotech, or life sciences.
- ** Technical Expertise**:

- Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, Scikit-learn, etc.).
- Experience with data engineering, ETL pipelines, and big data technologies (Spark, Kafka, Databricks, etc.).
- Proficiency in programming languages such as Python, R, or Java.
- Knowledge of cloud AI services (AWS Bedrock, Azure OpenAI, Google Vertex AI).
- Deploy a Lightweight LLM in a Pharma SaaS Platform
- ** MLOps & DevOps**: Familiarity with CI/CD, containerization (Docker, Kubernetes), vector databases, and real-time model monitoring.
- ** Regulatory & Ethical AI**: Understanding of AI governance, responsible AI principles, and compliance requirements for GenAI in pharma.
- ** Problem-Solving**: Strong analytical and problem-solving skills with the ability to design innovative GenAI solutions for life sciences use cases.
- ** Communication & Leadership**: Excellent communication skills to articulate GenAI strategies and solutions to technical and non-technical stakeholders.

**Preferred Qualifications**
- Knowledge of **AI explainability, retrieval-augmented generation (RAG), knowledge graphs, and synthetic data generation** in life sciences.
- AI/ML certifications from AWS, Google, or Microsoft.
- Understanding of **biomedical ontologies, semantic AI models, and federated learning**.
- Exposure to fine-tuning the LLM models will be a big plus
- Exposure to SLM or domain LLM model will be a big plus
- ** BioGPT & PubMedBERT**: NLP for biomedical literature and clinical trial analysis
- ** Custom SLMs**: Fine-tune **Mistral 7B, Phi-2, or Gemma** on pharma datasets

**_ Commitment to Diversity and Inclusion:_**:

- Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve._

**_Accessibility and accommodation_**:
Division

Operations

Business Unit

CTS

Location

India

Site

Hyderabad (Office)

Company / Legal Entity

IN10 (FCRS = IN010) Novartis Healthcare Private Limited

Functional Area

Data and Digital

Job Type

Full time

Employment Type

Regular

Shift Work

No

**Accessibility and accommodation**:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.