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Salary
$135k – $180k per year
Location
Hybrid (New York, United States)
Seniority
Staff · 7+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 19, 2026. Dassault Systemes scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Dassault Systemes is a French software company founded in 1981 as a spin-off from the aircraft maker Dassault Aviation, created to commercialise the three-dimensional design tools its engineers had built in house. It sells the CATIA and SOLIDWORKS design suites, SIMULIA simulation, ENOVIA lifecycle management and DELMIA manufacturing planning, all now delivered through the 3DEXPERIENCE platform that treats a product as one connected model from concept to service. The group has extended the same virtual twin idea into life sciences through the Medidata clinical trial platform and into urban and healthcare simulation, and it is headquartered in Velizy-Villacoublay near Paris.

Lead AI & Data Engineer

United States, NY, New York

Regular

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Key Job Details

Location:

United States, NY, New York

Job type:

Regular

Product:

MEDIDATA

Experience level:

Not specified

Posted on:

10/19/2026

Ref ID:

550610

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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.

About the Team:

We are seeking a Lead AI & Data Engineer to design, build, and deploy production-grade AI solutions and data products. In this role, you will lead the development of AI-powered solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration, and modern data architectures to enable new AI-driven capabilities across our Virtual Twin ecosystem.

The ideal candidate combines deep data engineering and AI-native development expertise to build scalable, secure, and reliable AI-enabled data solutions. You will drive technical architecture, data pipeline development, AI integration, and engineering best practices, translating complex business and clinical research requirements into production-ready solutions. You will work closely with product management, data science, platform engineering, and clinical experts, to deliver innovative capabilities that enable intelligent workflows and data-driven decision-making.

Responsibilities:

  • Engineer scalable, automated data pipelines and AI-powered solutions using modern AI technologies, vector databases, and automation, applying CI/CD practices and tools such as Python, SQL, and Git.
  • Design, develop, and deploy production-grade AI-powered solutions leveraging LLMs, RAG, and agentic workflows.
  • Implement and maintain integrations via API and MCP that connect applications and agents to enterprise data, tools, and skills in line with governance, security and compliance controls.
  • Implement agent orchestration and workflow patterns using frameworks such as LangGraph, LangChain, or equivalent technologies.
  • Develop agent-driven metadata management solutions to maintain data catalogs, business glossaries, lineage documentation, and governance policies.
  • Apply advanced skills in data architecture, data science engineering, data modeling, and data quality using modern cloud-native technologies.
  • Document and communicate technical work clearly to stakeholders at all levels, both technical and non-technical.
  • Collaborate effectively in Agile environments and cross-functional teams

Qualifications:

  • 7+ years of experience in data engineering or data science, with a strong foundation in enterprise data architecture, including at least 2 years of hands-on experience in AI and data engineering.
  • Bachelor's degree in a technical or scientific field, such as Data Engineering, Data Science, Computer Science, or similar.
  • Hands-on experience developing AI-native solutions using LLMs, RAG, AI agents, and agent orchestration patterns.
  • Skilled in integrating AI/ML pipelines into production-grade data infrastructure with experience in API and MCP standards and integration, including model access controls, 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, with the ability to troubleshoot complex issues and to translate business requirements into secure, scalable, production-ready solutions.
  • Experience with healthcare or clinical trial data is not required, but interest to learn and understand how these data improves Life Sciences is paramount.

Nice to Have:

  • Experience with 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.

The salary range posted below refers only to positions that will be physically based in New York City. As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location. Pay ranges for candidates in locations other than New York City, may differ based on the local market data in that region.

The salary range range for this position physically based in NYC/ NJ Metro Area is $135,000-$180,000.

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.

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.

Inclusion statement

In order to provide equal employment and advancement opportunities to all individuals, employment decisions at 3DS are based on merit, qualifications and abilities. 3DS 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 (40 and above), disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. 3DS will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state laws and local ordinances. We are committed to fair employment practices and will evaluate all candidates based on their qualifications, regardless of past arrest or conviction history.

Salary Pay Transparency

Compensation for the role will be commensurate with experience. The total expected compensation range will be between $135000 and $180000, representing the base salary (or annualized salary based on estimated hourly compensation) and target bonus.

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Dassault Systèmes">

MEDIDATA generates the evidence and insights to help pharmaceutical, biotech, medical device and diagnostics companies, and academic researchers accelerate value, minimize risk, and optimize outcomes.

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