AI Architect

About the role

The AI Architect is a senior technical leadership role responsible for defining the architecture, strategy, and enterprise adoption of Small Language Models (SLMs) and advanced Agentic AI solutions. This role provides end-to-end ownership of model design, optimization, and deployment – specifically focused on the Auto-Coding AI Engine. This position will bridge the gap between cutting-edge research and healthcare compliance, ensuring our engine delivers clinical-grade accuracy while mentoring teams and influencing AI strategy across the organization.

Responsibilities

• Define and own the enterprise architecture and standards for building solutions using Large Language Model (LLM) and/or Small Language Model (SLM), optimized for accuracy, latency, and cost.
• Architect domain-specific models that translate complex clinical documentation into industry-standard medical codes (ICD-10, CPT).
• Drive high-level decisions for model selection, fine-tuning, compression (quantization/distillation), and inference optimization.
• Align all AI solutions with enterprise security, HIPAA compliance, and "Responsible AI" governance frameworks.
• Lead the design and deployment of ML, DL, and Agentic AI solutions that utilize reasoning frameworks (e.g., Chain-of-Thought).
• Apply deep mathematical and statistical knowledge to optimize model performance and ensure clinical-grade precision.
• Provide architectural governance for traditional ML, deep learning (CNN, RNN, LSTM), and NLP-based systems.
• Architect solutions involving embeddings, transformers, and large-scale language models.
• Lead the fine-tuning of models for complex healthcare use cases and specialty-specific requirements.
• Establish standards for prompt engineering, evaluation metrics, and real-time performance monitoring.
• Architect and govern ML/AI solutions on AWS or Azure platforms.
• Define and enforce CI/CD, model versioning, and lifecycle management to ensure production reliability.
• Act as the expert in Python, scientific computing (TensorFlow, PyTorch), and optimized SQL designs for complex analytical data access.
• Act as the technical mentor for Data Scientists and ML Engineers, fostering a culture of innovation and excellence.
• Lead design reviews and collaborate with product, security, and clinical stakeholders to drive delivery discipline in an Agile environment.

Qualifications

• Master’s degree in computer science or AI.
• 10-15 years in data science and machine learning, with at least 5 years in leadership or architectural capacity.
• Proven experience architecting and deploying production-grade AI systems at an enterprise scale with measurable business impact.
• Expert knowledge of Random Forest, SVM, Regression, Boosting, and Bagging.
• Mastery of CNN, RNN, LSTM, and GRU architectures.
• Extensive experience with transformers, language modeling, and Agentic AI.
• Expert-level Python programming and experience in Linux/GPU-based environments.
• Deep understanding of RCM and medical coding standards.