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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data/AI Engineer - **Company:** Fujifilm Holdings America Corporation - **Location:** Atlanta, GA, United States (Remote available) - **Salary:** $146,000.0 - $241,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, ARM Architecture, Automation of Tests, Microsoft Azure, Big Data, Cloud Computing, Code Review, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Data Systems, Software Debugging, Supervisory Control and Data Acquisition (SCADA), Infrastructure as a Service (IaaS), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, Performance Tuning, Software Engineering, SQL Databases, Data Streaming, Web Application Frameworks, Data Processing, Cloud Platform System, Large Language Models, Snowflake, Caching, Containerization, Kubernetes, Information Technology, Software Version Control, Data Pipelines, GXP, Docker - **Published:** June 5, 2026 - **Apply:** https://www.juju.com/job/00000000g5opuc ## About the Role + 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). Preferred Experience and Education: + Advanced degree (MS/PhD) preferred. + Relevant industry certifications (e.g., Snowflake, AWS, Azure) preferred. Knowledge, Skills and Abilities: + Design and implementation of scalable batch and streaming data pipelines. + Strong proficiency in Python and SQL/dbt for data processing, automation, and analytics. + Extensive experience in Airflow or similar orchestration tool. + Expertise in designing and developing data solutions on Snowflake, including data modelling, performance optimization, and cost-efficient usage. + Experience with modern AI technologies, including LLMs, embeddings, and vector databases. + Proven track of delivering cloud-based solutions (AWS, Azure). + Containerization and deployment of data and AI workloads using Docker. + Orchestration and operation of containerized workloads using Kubernetes. + Data quality management, observability, lineage, and governance. + Knowledge of biotech IT/OT systems (MES, LIMS, SCADA), and compliance frameworks (GxP, FDA, data privacy). + Strong problem-solving, optimization, and troubleshooting skills for large-scale data systems. + Effective communication with both technical and non-technical stakeholders, influencing at senior levels. + Passion for emerging technologies, continuous improvement, and building innovative engineering cultures. ## Description 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., 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. What you'll do: + 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)