RESPONSIBILITIES & TASKS:
AI Solution Development
Design, develop, test, and deploy AI/ML models supporting business and operational outcomes.
Build and maintain AI services, APIs, and microservices for enterprise consumption.
Develop Generative AI and Agentic AI solutions using approved enterprise platforms and frameworks.
Implement Retrieval Augmented Generation (RAG) architectures and knowledge retrieval solutions.
Develop prompt engineering, evaluation, and optimization approaches for AI systems.
AI Platform Engineering and MLOps
Develop and maintain AI model deployment pipelines and model lifecycle processes.
Build automated testing, deployment, monitoring, model versioning, and release management capabilities.
Support production deployment of models and AI services aligned to enterprise architecture standards.
Data Engineering and Integration
Design and develop data pipelines required for AI model training and inference.
Integrate AI solutions with enterprise applications, cloud platforms, APIs, databases, and data warehouses.
Support data preparation, feature engineering, and operationalization of AI models.
AI Operations, Monitoring, and Continuous Improvement
Monitor model performance, accuracy, reliability, cost, and operational stability.
Implement observability and monitoring frameworks for AI workloads.
Investigate production issues, perform root-cause analysis, and implement corrective actions.
Tune and optimize models and AI services for performance, quality, and usability.
Security, Governance, and Responsible AI
Ensure AI solutions align with enterprise AI governance, information security, privacy, and data protection requirements.
Apply responsible AI principles including fairness, transparency, explain ability, reliability, and human oversight.
Support AI risk assessments, security reviews, and compliance documentation.
Collaboration and Enablement
Work closely with business stakeholders, Data Scientists, solution architects, application teams, and platform engineers.
Participate in AI use case discovery, design workshops, technical reviews, and implementation planning.
Support knowledge sharing and AI capability development across regional subsidaries.
SKILLS & QUALIFICATIONS:
Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related discipline.
Experience developing production-grade AI/ML solutions, working with cloud-native platforms, and implementing machine learning models in enterprise environments.
Technical Skills
Python
Machine learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn
LLM and agent frameworks such as LangGraph, LangChain, Semantic Kernel, or AutoGen
API development and microservices
Vector databases and RAG architectures
MLOps platforms, CI/CD, and model lifecycle management
SQL and data engineering
Cloud services across AWS, Azure, or GCP
Container technologies such as Docker and Kubernetes
Git and DevOps practices
Job details are sourced from the employer's original posting.
Open job postingAbout the company
FUJIFILM is a global leader in imaging and information solutions. The company leverages its advanced technologies to develop and manufacture a wide range of products, including photographic film, digital cameras, medical imaging equipment, and graphic systems.