Senior AI Engineer with Machine Learning Expertise

- Develop AI applications such as copilots, search assistants, document intelligence, workflow automation agents, predictive models, and decision-support tools - Implement RAG pipelines using corporate data sources (SharePoint, data lake, document repositories, research systems, etc.) - Build and sustain end-to-end AI pipelines which include data ingestion, feature engineering, model training, evaluation, deployment, and monitoring - Integrate LLMs via APIs and platforms (Azure OpenAI, OpenAI, Anthropic, AWS Bedrock) into business workflows - Establish prompt engineering, grounding, and evaluation frameworks to enhance accuracy and reliability - Transform business use cases (e.g., medical affairs, regulatory, commercial, finance) into functional AI prototypes and production applications - Work collaboratively with Data Scientists to convert models into scalable production systems - Team up with Product Owners and SMEs to clarify requirements and success metrics - Create reusable AI components, prompt libraries, and solution patterns - Deploy and maintain AI solutions utilizing cloud platforms and contemporary APIs - Set up essential MLOps and LLMOps processes: versioning, monitoring, logging, and performance tracking - Integrate with identity, access control, and data-security platforms (RBAC, Purview, etc.) - Apply logging, observability, performance tracking, and cost optimization for AI workloads - Ensure the reliability, scalability, and security of AI systems in production environments - Confirm that AI solutions adhere to data classification, privacy, and governance policies - Assist in documentation for model usage, data sources, and risk assessments - Enforce guardrails to prevent data leakage, hallucinations, and misuse