Director, AI/ML Platform Engineering Lead

Job Summary

We are seeking a hands-on AI/ML Architect/Engineer to design, build, and scale our next-generation platforms for Generative AI, LLMOps, and MLOps within a pharmaceutical environment. This role is pivotal in enabling the responsible and efficient adoption of AI across R&D, commercial, and support functions. The ideal candidate will collaborate closely with data scientists, business partners, and other business and IT stakeholders to transform AI concepts into production-ready solutions using technologies such as DataIKU, Microsoft Azure AI Services, and AWS AI Services. This is a strategic and technical role focused on delivering real-world impact through robust, scalable AI platforms.

Key Responsibilities

• Architect and implement enterprise-scale AI/ML platforms to support GenAI, traditional ML, and hybrid use cases.
• Enable end-to-end LLMOps and MLOps capabilities, including model lifecycle management, CI/CD, prompt versioning, monitoring/observability, and governance.
• Develop and integrate AI workflows using DataIKU, Azure AI Services (e.g., OpenAI, Search, Cognitive Services, etc), Snowflake Cortex, and AWS AI Services (e.g., Amazon Bedrock, Amazon Comprehend, etc).
• Design and implement agentic architectures using frameworks such as LangChain, LangGraph, AutoGen, or Semantic Kernel—enabling multi-step reasoning, tool orchestration, memory persistence, and task planning.
• Build reusable tools, SDKs, and templates to support efficient development and deployment by cross-functional teams.
• Collaborate with business partners, data scientists, and product owners to identify, prioritize, and deliver high-value AI use cases.
• Ensure compliance with regulatory, data privacy, and responsible AI guidelines throughout the AI lifecycle.
• Provide hands-on support and mentorship to project teams deploying AI solutions across the business.
• Contribute to enhancing the AI readiness and Data literacy across the organization.
• Continuously evaluate emerging GenAI technologies, vector search strategies, and foundation models to enhance platform capabilities.
• Establish and maintain the AI platform strategic roadmaps aligned with the company's business priorities and the vision for AI, collaborating closely with relevant business and IT stakeholders.
• Implement FinOps for AI platforms to ensure proper financial discipline for cost forecasting and tracking, including providing cost metrics to the teams utilizing the platforms.
• Work closely with the Managed Service Providers to manage platform demand and perform Ops & Support resource planning.

Required Qualifications

• 7+ years of experience in software engineering, data science, or AI/ML engineering, including 3+ years in a senior engineering lead or architect role.
• Proven experience productionizing Generative AI and LLM solutions, including agent-based systems leveraging LangChain Agents, AutoGen, or Semantic Kernel with tool use, memory, and task chaining.
• Hands-on expertise with DataIKU, including plugin development, automation scenarios, and Python integration.
• Strong proficiency in Azure AI Services and AWS AI Services.
• Proficient in Python, with practical experience in developing scalable AI services using FastAPI, Docker, Kubernetes, and CI/CD tools.
• Familiarity with vector databases (e.g., OpenSearch, Pinecone, etc) and enterprise search strategies using embeddings.
• Deep understanding of LLMOps/MLOps best practices, including experimentation tracking, performance monitoring, model safety, and prompt evaluation.
• Demonstrated ability to set technical standards, define architectural patterns, and foster enterprise-wide alignment.
• Experience with vendor selection and management.
• Excellent communication and stakeholder engagement skills, especially in cross-functional teams involving business and technical partners.
• Strong ability to influence outside of functional area regarding policies, practices and procedures as it pertains to introduction of new AI technologis and adoption of Responsible AI principles.
• Strong collaborative mindset, able to work cross-functionally across business, data, and engineering teams.
• Results-oriented, with a track record of delivering impactful solutions in complex environments.
• Experience working in or supporting regulated industries, preferably life sciences, healthcare, or pharmaceuticals.

Our Culture

About Our Culture

As we work to develop solutions that enhance peoples' lives, we also work to care for our teammates' professional and personal growth and well-being.

Growth and Development

As a member of our team, we see your growth and learning as being critic