Position Overview
The Director, Data & AI Engineering is responsible for designing, developing, and scaling enterprise data pipelines, and analytics and AI/ML algorithms to create operation efficiencies and create business value. The role ensures that data pipelines, models, and AI/ML engineering frameworks are reliable, secure, compliant, and optimized for business value delivery. This position leads a team of engineers to enable seamless integration of data from biotech systems, support AI/ML lifecycle management, and ensure the organization’s data foundation supports innovation and regulatory compliance.
Job Description
Principal Accountabilities:
Design, implement, and maintain enterprise-scale data pipelines for data ingestion, processing, storage to support advanced analytics and ML workloads. (20%)
Lead and mentor a team of data engineers, data scientists and AI/ML engineers to build scalable, secure, and compliant solutions. (20%)
Design, implement, and maintain cloud-native solutions (AWS, Azure) for applying AI/ML to solve business problems in a biotech environment. (15%)
Ensure integration of biotech systems (MES, LIMS, SCADA, ERP, QMS) into centralized data platforms. (10%)
Implement MLOps practices to streamline model deployment, monitoring, and lifecycle management. (10%)
Collaborate with product managers, product engineers, platform architects, and business stakeholders to align data and AI engineering solutions with business requirements. (10%)
Drive performance optimization, cost management, and reliability of cloud-based data/AI infrastructure. (5%)
Partner with cybersecurity and compliance teams to ensure adherence to GxP, FDA 21 CFR Part 11, and data privacy regulations. (3%)
Stay current with emerging technologies (data mesh, real-time streaming, digital twins, generative AI platforms) and introduce relevant innovations (2%)
All other duties that may be assigned from time to time (5%)
Minimum Education and Experience Requirements:
Bachelor’s degree in Computer Science, Data Engineering, AI/ML Engineering, or related technical discipline required.
10+ years of professional experience in data engineering, AI/ML engineering, or cloud platform engineering.
Minimum of 6 years in a technical leadership or team lead role.
Strong experience with cloud platforms (AWS, Azure)
Proven experience implementing MLOps/DevOps pipelines for scalable AI/ML deployment.
Familiarity with biotech or life sciences systems and regulatory compliance frameworks (GxP, FDA, EMA).
Preferred Education and Experience:
Master’s degree in Data Science, Artificial Intelligence, or Cloud Computing preferred.
Knowledge, Skills and Abilities:
Technical: Expertise in distributed systems, data pipelines, cloud architecture, APIs, and MLOps frameworks.
AI/ML Engineering: Proficiency in deploying ML models at scale, container orchestration, monitoring, and lifecycle management.
Biotech / Regulatory: Knowledge of biotech IT/OT systems (MES, LIMS, SCADA), and compliance frameworks (GxP, FDA, data privacy).
Leadership: Ability to lead, mentor, and develop high-performing technical teams.
Analytical: Strong problem-solving, optimization, and troubleshooting skills for large-scale data systems.
Soft Skills: Effective communication with both technical and non-technical stakeholders, influencing at senior levels.
Other: Passion for emerging technologies, continuous improvement, and building innovative engineering cultures.
To all agencies: Please, no phone calls or emails to any employee of FUJIFILM about this requisition. All resumes submitted by search firms/employment agencies to any employee at FUJIFILM via-email, the internet or in any form and/or method will be deemed the sole property of FUJIFILM, unless such search firms/employment agencies were engaged by FUJIFILM for this requisition and a valid agreement with FUJIFILM is in place. In the event a candidate who was submitted outside of the FUJIFILM agency engagement process is hired, no fee or payment of any kind will be paid.