Life Sciences AI Solution Architect

Title: Life Sciences AI Solution Architect

Experience Required: 13+ Years

Location: Greater Noida, Hyderabad, Pune, 5 days work from office

Role Summary:

We are seeking a highly experienced Life Sciences AI Solution Architect with deep expertise in AI/ML solutioning and architecture within the pharmaceutical and biotech domains . The ideal candidate will have a strong understanding of pharma data , relevant regulatory frameworks , and hands-on experience in designing and deploying AI/ML solutions across the life sciences value chain including R&D, manufacturing, supply chain, commercial operations, and patient safety . This role demands strategic thinking, technical leadership, and cross-functional collaboration to drive innovation and transformation.

Key Responsibilities:

• Design and architect end-to-end AI/ML solutions for pharma/biotech use cases.
• Apply MLOps methodologies for efficient model development, deployment, and monitoring.
• Leverage Cognitive AI techniques such as NLP, Computer Vision, Speech, and Conversational AI.
• Develop and implement Document AI and Generative AI solutions, including custom LLMs.
• Ensure seamless integration of AI solutions into cloud platforms (AWS, Azure, GCP).
• Deliver and maintain production-grade ML systems with high scalability and reliability.
• Provide technical leadership and mentorship to AI/ML teams.
• Collaborate with data scientists, ML engineers, and business stakeholders to transition prototypes to production.
• Prepare comprehensive documentation for architecture, design, and implementation.
• Stay current with emerging trends in AI, LLMs, MLOps , and life sciences technologies .

Mandatory Skills:

• 8+ years in AI/ML , with 3+ years in life sciences AI (pharma/biotech).
• Proven experience in AI, ML, MLOps, Text Analytics, Generative AI .
• Strong programming skills in Python and Java .
• Experience with ML frameworks: TensorFlow, PyTorch, Keras, Scikit-learn .
• Hands-on with cloud platforms: AWS, Azure, GCP .
• Proficient in ML architectures: Ensemble Models, SVM, CNN, RNN, Transformers .
• NLP tools: NLTK, SpaCy, Gensim .
• MLOps tools: Kubeflow, MLflow, Azure ML .
• Experience in Responsible AI , LangChain , and Vector Databases .
• Workflow tools: Airflow .
• Microservices architecture and API development using FastAPI, Flask, Django .
• Database expertise: SQL, NoSQL (MongoDB, Postgres, Neo4j) .