Principal Data Scientist

Design and deliver a reusable agentic AI orchestration framework with multi-agent pipelines, detection/validation stages, confidence routing, and escalation to advanced reasoning models.

Establish API strategy, versioning, backward compatibility, deprecation, authentication/authorization patterns, and governance controls for consistent adoption across teams.

Set technical direction and architecture standards for shared AI capabilities and evaluate framework evolution versus adherence to standards.

Master’s or Ph.D. in CS, AI, ML or related field; equivalent practical experience in large-scale AI/ML platforms accepted.

Proven experience designing and delivering a reusable framework/SDK/platform adopted by at least three engineering teams.

Demonstrated end-to-end production ML system architecture experience and ability to set technical direction for others.

Strong expertise in Python and ML frameworks/tools (PyTorch, TensorFlow, scikit-learn); experience with agentic AI architectures and multi-agent orchestration.

Experienced in building foundational AI/ML platforms used reliably by multiple teams, indicating strong architectural ownership.

Deep technical knowledge across AI/ML fundamentals including representation learning, embeddings, LLMs, and security/governance for agentic AI.

Able to operate at strategic and technical levels across multidisciplinary teams to define standards, APIs, and enforceable security controls.