Lead AI Engineer

Role Overview
We are seeking an experienced Technical Lead - Generative AI to lead the design and implementation of enterprise-scale AI solutions within an existing AI platform. The role will own the end-to-end technical approach, including RAG architecture, prompt engineering, evaluation frameworks, retrieval optimization, and AI application configuration, while guiding engineering standards and delivery.

Key Responsibilities

• Lead the design and implementation of LLM-powered and RAG-based solutions, including retrieval, grounding, prompt architecture, and evaluation.
• Define chunking, indexing, embeddings, reranking, source attribution, and hallucination mitigation strategies.
• Design scalable prompt workflows for long-form document generation and structured content authoring.
• Establish and maintain AI evaluation frameworks, golden datasets, regression testing, and human review processes.
• Make and document key technical decisions and present recommendations to senior stakeholders.
• Drive engineering best practices across version control, prompt management, configuration management, and documentation.
• Assess technical feasibility, identify risks, and provide solution guidance during requirements definition.
• Build automation, data preparation, and evaluation tooling while extending existing enterprise AI platforms.

Required Qualifications

• 4+ years of hands-on experience delivering production-grade Generative AI solutions.
• Strong experience with LLMs, RAG, Prompt Engineering, AI Architecture, and Evaluation Frameworks.
• Deep expertise in retrieval systems, embeddings, vector databases, semantic search, and grounding techniques.
• Experience with Azure OpenAI/OpenAI, Databricks, GitHub Copilot, or similar enterprise AI platforms.
• Strong Python programming and Git/version control skills.
• Proven technical leadership experience managing cross-functional or client-facing AI initiatives.
• Excellent communication skills with the ability to influence senior stakeholders.

Preferred Qualifications

• Experience in Life Sciences, Pharmaceuticals, Medical Writing, HEOR, or Regulatory Content.
• Knowledge of Agentic AI, Knowledge Graphs, and Multi-Agent Architectures.
• Experience in regulated environments (GxP, compliance-focused platforms).
• Exposure to workflow automation tools such as Power Automate, UiPath, or SharePoint integrations.
• Experience with AI model evaluation, fine-tuning, distillation, and AI engineering standards.