Principal Data/AI Engineer

Fujifilm

About The Position

The Principal Data/AI Engineer helps drive the technical strategy and architecture of enterprise-scale data and AI platforms that power mission-critical data products, analytics, and AI-driven solutions. In this role, you will operate as a technical expert in planning, designing, developing, and debugging new and existing data pipelines. You will advocate for data and AI engineering best practices, including idempotent modular pipeline design, version control, automated testing, CI/CD, IaaS, data quality checks and observability. You will help mentor junior engineers through design guidance, code reviews, pairing, and enabling Agile frameworks to promote iterative delivery and continuous improvement. The work we do at FUJIFILM Biotechnologies has never been more important—and we are looking for talented candidates to join us. We are growing our locations, our capabilities, and our teams, and looking for passionate, mission-driven people like you who want to make a real difference in people’s lives. Join FUJIFILM Biotechnologies and help make the next vaccine, cure, or gene therapy in partnership with some of the most innovative biopharma companies across the globe. We are proud to cultivate a culture that will fuel your passion, energy, and drive - what we call Genki. Fujifilm is globally headquartered in Tokyo with over 70,000 employees across four key business segments of healthcare, electronics, business innovation, and imaging. We are guided and united by our Group Purpose of “giving our world more smiles.” Visit: https://www.fujifilm.com/us/en/about/region/careers You will work closely with cross-functional team of business and IT peers and expected to lead by example - balancing delivery speed of new features with long-term platform health and technical excellence.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, AI/ML Engineering, or related field.
12+ years of professional experience in data/software engineering, AI/ML engineering, or cloud platform engineering.
Proven experience using Python and SQL
Extensive experience building and maintaining data pipelines using modern frameworks (e.g. Airflow, dbt).
Proven experience with data modelling for analytics and AI use cases.
Strong experience with cloud platforms (AWS, Azure).
Proven experience delivering production-grade data solutions.
Familiarity with biotech or life sciences systems and regulatory compliance frameworks (GxP, FDA, EMA).

Nice To Haves

Advanced degree (MS/PhD) preferred.
Relevant industry certifications (e.g., Snowflake, AWS, Azure) preferred.

Responsibilities

Architect, build, and maintain highly scalable batch and streaming pipelines on the Snowflake Data Platform (Snowpipe, Tasks, Streams, Dynamic Tables, Snowpark, Iceberg).
Architect and deliver ML/GenAI solutions using managed cloud services (AWS, Azure, Snowflake Cortex).
Implement modern data modeling and architecture patterns; establish and enforce standards for data quality (tests, expectations, SLAs/SLOs), observability (metrics, logs, traces), and lineage.
Ensure integration of biotech systems (MES, LIMS, SCADA, ERP, QMS) into centralized data platform.
Collaborate with product managers, product engineers, platform architects, and business stakeholders to align data and AI engineering solutions with business requirements.
Enable modern AI use cases - feature stores, vector search/RAG, model serving, safety/guardrails, and continuous monitoring for drift, bias, and performance.
Optimize storage tiers, compute clusters/warehouses, caching, and workload orchestration for latency and throughput.
Partner with cybersecurity and compliance teams to ensure adherence to GxP, FDA 21 CFR Part 11, and data privacy regulations.
Lead design reviews, incident postmortems, and cross-team architecture forums.
Stay current with emerging technologies (data mesh, real-time streaming, digital twins, generative AI platforms) and introduce relevant innovations.
And other job duties that may be assigned from time to time.