Lead AI Solutions Systems Engineer

What you'll do

• Translate complex business problems into rigorous mathematical, data engineering, and algorithmic requirements for AI initiatives.
• Evaluate the technical feasibility, data readiness, and infrastructure viability of proposed AI projects.
• Design high-level solution blueprints, including build-vs-buy trade-offs and MLOps release pipelines.
• Rapidly prototype initial Proofs of Concept (PoCs) and co-author code to accelerate industrialization.
• Define technical validation metrics such as ML quality, latency, data bias, and LLM safety safeguards.
• Manage the transition from custom-coded frameworks to robust no-code agentic structures.
• Coordinate with global teams to align local implementations with corporate data governance and API standards.
• Mentor and coach team members to improve their engineering and algorithmic capabilities.

What we're looking for

• Master's degree in AI (ML/Data Science), Computer Science, or a highly quantitative field.
• Specialization in NLP, Generative AI, or Agentic AI (preferred).
• Minimum of 10 years of experience in advanced analytics initiatives.
• Proven experience in production-grade architecture and engineering for at least one Generative AI or Agentic AI system.
• Experience across Corporate and Operations business branches, with manufacturing experience highly preferred.
• Proficiency in Python, PyTorch, TensorFlow, SciKit/MLlib, and the Google Enterprise Agent Platform (Vertex AI).
• Expertise in software development lifecycles, API design, containerization (Docker, Kubernetes), and MLOps pipelines.
• Authorized to Work in the US.