12 to 16 years of experience in Artificial Intelligence, Machine learning technologies, GenAI technologies.
Proven experience as an Enterprise Architect, Solution Architect, or a similar role, with a focus on AI/ML and generative AI.
Core expertise in architecting AI/ML, Deep learning GEN AI Solutions end-to-end.
Proven skills building machine learning, deep learning models leveraging large datasets.
Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
Proficiency in NLP and computer vision techniques to extract insights from unstructured clinical/healthcare data.
Experience in designing algorithms for predictive analytics for efficient data analysis and processing.
Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
Proven expertise with LLMs (Google Vertex AI, Gemini / Microsoft Azure Open AI /and other LLM models) including API access for GenAI.
Proven expertise in CI/CD pipeline design and management in the Generative AI space including experience with LLMOPS.
Understanding and working knowledge of Agentic AI and its usage in the intelligent automation of business workflows.
Should have working knowledge of how to integrate RAG and MCP into AI solution designs to address specific business needs.
Strong hands-on experience with Cloud databases such as Snowflake, Aurora, Google BigQuery etc.
Strong Hands-on experience with SAS GRID/SAS VIYA, AWS Sage maker, Jupyter Notebooks, and platforms like AWS bedrock and Azure data science workbench.
Familiarity with data structures, data modeling, and software architecture
Strong understanding of HIPAA regulations and healthcare data privacy laws is a must-have for this role, as the healthcare domain requires strict adherence to data privacy and security regulations.
Strong experience with AI/MLOps concepts and Generative AI technology.
Must be skillful in documenting architectural artifacts, establishing reference architectures.
Well-versed in following enterprise architecture governance, enforce best practices/standards, prepare architecture blueprints, strategies, and roadmaps.
Excellent written and oral communication skills to convey key choices, recommendations, and technology concepts to technical and non-technical audiences.
Experience utilizing API development and integration using tools such as MuleSoft and REST APIs
Proven skills of leading junior team members guiding/orienting them ensuring smooth timely completion of tasks.

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