Associate Director, AI Enablement – Commercial & Medical Affairs

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the design and execution of enterprise AI/ML and GenAI platforms, encompassing RAG pipelines, LLM orchestration layers, and agentic AI frameworks.

• Develop scalable, reusable AI services and APIs that facilitate swift development and deployment of AI applications throughout the organization.

• Establish and implement LLMOps/MLOps practices, including model lifecycle management, monitoring, evaluation, versioning, and CI/CD.

• Design solutions that integrate vector databases, knowledge repositories, and enterprise data platforms for context-aware AI applications.

• Guarantee seamless integration of AI functionalities with existing data systems, CRM, and marketing technology ecosystems.

• Create frameworks, toolkits, and best practices to empower data scientists, engineers, and analysts in efficiently building AI-powered applications.

• Promote self-service AI capabilities, including prompt frameworks, reusable components, and standardized pipelines.

• Enhance developer productivity and experimentation velocity through well-designed AI abstractions and tools.

• Lead the internal adoption of AI platforms through comprehensive documentation, training, and enablement initiatives.

• Design and operationalize RAG architectures for enterprise knowledge retrieval and grounded generation.

• Develop and scale agentic AI systems that support multi-step reasoning, orchestration, and task automation.

• Assess and implement LLM strategies (fine-tuning vs. RAG vs. hybrid approaches) tailored to specific use case requirements.

• Ensure the robustness of GenAI systems using evaluation frameworks, guardrails, and monitoring mechanisms.

• Collaborate with data engineering teams to ensure the provision of high-quality, accessible, and governed data pipelines for AI utilization.

• Enable both real-time and batch AI applications through event-driven and streaming architectures.

• Optimize the performance, scalability, and cost-effectiveness of AI workloads across cloud environments.

• Define and enforce AI governance frameworks that include model validation, explainability, and auditability.

• Ensure adherence to data privacy, security, and regulatory standards (e.g., HIPAA, GDPR, GxP where applicable).

• Implement safeguards to mitigate GenAI risks, including hallucination, bias, and data leakage.

• Act as a liaison between technology, data science, and business teams, facilitating scalable AI adoption.

• Collaborate with stakeholders to transform business needs into platform capabilities and reusable solutions (avoiding one-off builds).

⛳️ Requirements

• A Master's degree or higher with 6+ years of experience in AI/ML engineering, platform development, or data engineering, ideally in enterprise settings.

• Extensive hands-on experience with RAG architectures and LLM frameworks (e.g., LangChain, LlamaIndex).

• Familiarity with vector databases (Pinecone, FAISS, Weaviate, etc.).

• Proficient in LLMOps/MLOps tooling and production model lifecycle management.

• Experience in building scalable AI platforms, APIs, and microservices architectures.

• Proficient in Python, SQL, and contemporary cloud platforms (AWS, Azure, or GCP).

• Experience with data platforms such as Databricks, Snowflake, or similar.

• Understanding of distributed systems, real-time architectures, and data pipelines.

• Strong grasp of AI system evaluation, monitoring, and optimization processes.

• Proven capability in leading platform-centric AI initiatives, beyond just analytics use cases.

• Ability to drive standardization, reuse, and scalability in AI implementations.

• Excellent collaboration skills across engineering, data science, and business teams.

• Experience in influencing architectural decisions and promoting the adoption of shared platforms.

• Capability to translate complex AI insights into clear, strategic recommendations for business leaders.

• Strong influencing skills, effectively collaborating with stakeholders and cross-functional teams.

• Experience leading AI/analytics initiatives that yield measurable business impact.

• Outstanding communication and storytelling skills, making AI-driven insights easily understandable and actionable for executives.

🏝️ Benefits

• Medical

• Dental

• Vision

• 401(k)

• FSA/HSA

• Life Insurance

• Paid Time Off

• Wellness