Location: This is a hybrid remote/in-office role.

Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week following Company policy.

About our Company:

Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating over 25 years of ground-breaking technological innovation across more than 38,000 trials and 12 million patients, Medidata offers industry-leading expertise, analytics-powered insights, and one of the largest clinical trial data sets in the industry. More than 1 million registered users across approximately 2,300 customers trust Medidata's seamless, end-to-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. A Dassault Systèmes brand (Euronext Paris: FR0014003TT8, DSY.PA), Medidata is headquartered in New York City and has been recognized as a Leader by Everest Group and IDC. Discover more at www.medidata.com. Listen to our latest podcast, from Dreamers to Disruptors, and follow us at @Medidata.

Our team:

This position is for the Data Nexus team within Study Experience Engineering, focused on building Medidata's next generation of AI-enabled data platforms and intelligent applications. The team works across Generative AI, Agentic workflows, AWS, Snowflake, Apache Iceberg, Airflow, Python, and Java to power scalable data ingestion, transformation, APIs, analytics, and automation. You will work in a highly collaborative environment with engineering, product, QA, PMO, and platform teams to solve complex data and application challenges and bring AI-driven capabilities into Medidata's clinical technology ecosystem.

Who we are looking for:

Reporting to the Director, Engineering, the Senior AI & Data Engineer – Study Experience will design, build, and operate production-grade AI and data solutions that enable intelligent applications, automation, analytics, and operational workflows.

This is a hands-on engineering role with a primary focus on Generative AI and agentic applications, supported by strong data and application engineering capabilities. You will build AI-enabled services, connect enterprise data and applications to LLM-powered workflows, and develop scalable data pipelines using modern cloud technologies.

What You'll Do

• Design and build production Generative AI applications, AI agents, and LLM-powered workflows for enterprise use cases.

• Develop AI services and backend capabilities using Python, APIs, and cloud-native engineering patterns.

• Build RAG and retrieval workflows that securely connect enterprise data and applications to AI solutions.

• Implement agentic workflows involving tool calling, structured outputs, retrieval, workflow execution, and external system integrations.

• Work with AI orchestration frameworks and emerging standards such as LangGraph, LangChain, MCP, or similar technologies.

• Implement testing, evaluation, guardrails, monitoring, and observability to improve the quality and reliability of production AI solutions.

• Design and maintain scalable data pipelines and ETL/ELT workflows that support AI, analytics, and operational applications.

• Build data solutions using AWS, Snowflake, Python, SQL, and modern data engineering technologies.

• Develop and integrate APIs and backend services, including Java-based applications where needed.

• Apply strong software engineering practices including automated testing, CI/CD, Git, security, documentation, and production support.

• Use AI-assisted development tools and coding agents as part of day-to-day design, coding, testing, debugging, and code review.

• Collaborate with engineers, architects, product teams, and business stakeholders on technical designs and production solutions.

• Mentor engineers through technical guidance, code reviews, and knowledge sharing.

What We're Looking For

• 5+ years of professional experience in software engineering, AI engineering, data engineering, or a related technical discipline.

• Strong hands-on experience developing production applications and services using Python.

• Practical experience building or integrating Generative AI applications, LLM workflows, agentic systems, or AI-enabled services.

• Good understanding of RAG, embeddings, vector search, retrieval, grounding, and LLM orchestration concepts.

• Experience with at least one AI orchestration framework or emerging protocol such as LangGraph, LangChain, MCP, or equivalent technologies.

• Strong SQL and data engineering fundamentals, including experience building production data pipelines and integrations.

• Experience working with AWS and modern data platforms such as Snowflake.

• Experience developing or integrating REST APIs and backend services.

• Strong understanding of modern software engineering practices including automated testing, CI/CD, version control, observability, and production support.

• Ability to independently troubleshoot complex issues across AI services, APIs, data pipelines, and cloud environments.

• Strong communication and collaboration skills and the ability to contribute effectively to technical design discussions.

Preferred Skills

• Experience with managed AI platforms or models such as AWS Bedrock, Anthropic Claude, OpenAI APIs, Azure OpenAI, or similar technologies.

• Experience with vector and search technologies such as OpenSearch, pgVector, Pinecone, Weaviate, or similar platforms.

• Experience building MCP servers, tools, or enterprise AI integrations.

• Familiarity with data technologies such as Airflow, Kafka, Apache Iceberg, or dbt.

• Experience with Docker, Kubernetes, Terraform, or similar cloud-native technologies.

• Familiarity with AI evaluation, prompt/version management, structured logging, and AI observability.

• Understanding of AI governance, data privacy, security, responsible AI, and human-in-the-loop patterns.

• Experience working in regulated industries such as Life Sciences or Healthcare.

As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location.

• The salary range for positions that will be physically based in the NYC Metro Area is $114,750-153,000
• The salary range for positions that will be physically based in all other locations within the United States is $102,750-137,000.

Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.

#LI-MM1 #LI-Hybrid

Equal Employment Opportunity: In order to provide equal employment and advancement opportunities to all individuals, employment decisions at Medidata are based on merit, qualifications and abilities. Medidata is committed to a policy of non-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age, disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. Medidata will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

We will accept applications on an ongoing basis until we fill the position.