Lead the design and delivery of production-grade AI and data products within Medidata’s Virtual Twin ecosystem.

Build scalable, automated data pipelines and AI-powered solutions using modern AI technologies, vector databases, and automation
Apply CI/CD practices and tooling with Python, SQL, and Git
Design, develop, and deploy production-grade AI solutions using LLMs, RAG, and agentic workflows
Implement and maintain integrations via API and MCP to connect applications and agents to enterprise data, tools, and skills under governance, security, and compliance controls
Orchestrate agent workflows using frameworks such as LangGraph, LangChain, or equivalent technologies
Create agent-driven metadata management for data catalogs, business glossaries, lineage documentation, and governance policies
Use advanced data architecture and data science engineering skills for data modeling, data quality, and cloud-native implementations
Document and communicate technical work clearly to stakeholders across technical and non-technical audiences
Collaborate effectively in Agile environments and cross-functional teams

7+ years in data engineering or data science, including a strong foundation in enterprise data architecture
At least 2 years hands-on experience in AI and data engineering
Bachelor’s degree in a technical or scientific field (e.g., Data Engineering, Data Science, Computer Science, or similar)
Hands-on experience building AI-native solutions with LLMs, RAG, AI agents, and agent orchestration patterns
Experience integrating AI/ML pipelines into production-grade data infrastructure, including API and MCP integration and model access controls
Experience with context management, auditability, security, compliance monitoring, and lifecycle management
Experience implementing AI governance and guardrails, including access controls, data privacy, auditability, and policy enforcement across AI services and agents
Proficiency in Python, SQL, and modern data engineering practices, including CI/CD and Git-based development
Hands-on experience with tools and concepts such as Airflow, CDC, batch processing, and job scheduling
Strong problem-solving, communication, and collaboration skills, including troubleshooting complex issues and translating business needs into secure, scalable solutions
Healthcare or clinical trial data experience is not required, but interest in learning how these data improve Life Sciences is important

Hybrid remote/in-office in New York, NY
Medidata follows a hybrid office policy requiring in-person employees to work on site a certain number of days per week based on company policy

Knowledge graphs, advanced vector search, and retrieval optimization techniques
Familiarity with clinical research data standards and formats such as CDISC SDTM and ADaM
Experience with AI evaluation frameworks, benchmarking, and continuous monitoring of AI solution performance
Experience optimizing cloud infrastructure, AI workloads, and data processing costs
Familiarity with semantic layers, metadata-driven architectures, and automated data cataloging

Salary range: USD 135,000 - 180,000 per year
Base pay is one component of Medidata’s Total Rewards
Most sales positions may be eligible for commission under applicable plan documents
Many non-sales positions may be eligible for annual bonuses

Lead AI & Data Engineer

Job Description