Senior AI/ML Architect — GenAI & MLOps for BFSI

Veriipro; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Veriipro is seeking a Senior AI/ML Architect to lead the design, development, and deployment of cloud-native AI/ML solutions for BFSI clients. The ideal candidate will have over 15 years of experience in AI/ML architecture, proven leadership capabilities, and the ability to mentor cross-functional teams.

This role involves architecting scalable AI/ML solutions, integrating them into production, and ensuring compliance and governance across projects. Hands-on expertise in MLOps and cloud environments (AWS, Azure, GCP) is essential.

Qualifications

• Extensive experience in AI/ML architecture and deployment in BFSI.
• Strong leadership capabilities and ability to present complex architectures.
• Mentoring experience with cross-functional teams.

Responsibilities

• Lead design and deployment of scalable AI/ML solutions.
• Drive full project lifecycle from design to monitoring.
• Define standards for AI/ML governance and compliance.
• Integrate models into production ensuring scalability and security.
• Mentor ML engineers and establish engineering standards.

Skills

AI/ML architecture and solution design

Python and ML/DL frameworks (scikit-learn, TensorFlow, PyTorch, HuggingFace)

Cloud-native AI/ML architecture (AWS, Azure, GCP)

MLOps expertise

GenAI/LLM architecture

Graph/network analytics (Neo4j, TigerGraph)

Big data/ML pipelines (Spark, PySpark, Scala)

BFSI domain knowledge

Education

15+ years of experience in AI/ML

Job description

Veriipro is seeking a Senior AI/ML Architect to lead the design, development, and deployment of cloud-native AI/ML solutions for BFSI clients. The ideal candidate will have over 15 years of experience in AI/ML architecture, proven leadership capabilities, and the ability to mentor cross-functional teams.

This role involves architecting scalable AI/ML solutions, integrating them into production, and ensuring compliance and governance across projects. Hands-on expertise in MLOps and cloud environments (AWS, Azure, GCP) is essential.