Solstice Advanced Materials is looking to solve the problem of delivering end-to-end AI initiatives across the enterprise for GenAI and Classic AI/ML solutions while ensuring responsible AI and data engineering best practices.
Requirements
- Expert-level proficiency in Python, SQL with hands-on knowledge of modern data engineering tools and practices.
- Foundational understanding of AI concepts like Self-attention, Transformer architecture, Reinforcement Learning with Human Feedback, Deep Learning, MCP etc.
- Prior experience with Azure AI Search, Qdrant, Postgres Vector or similar vector databases.
- Hands-on experience with AI/ML platforms (Azure OpenAI, Databricks, MLOps) and implementing enterprise-scale machine learning solutions.
- Experience implementing end-to-end AI & Gen AI solutions especially around RAG, Graph RAG systems or similar semantic search systems.
- Experience with AI/ML Framework such as Pytorch, Tensorflow or Scikit Learn.
- Advanced experience with Infrastructure as Code (IaC) practices, Terraform/Bicep, Docker/Kubernetes, and cloud-native architecture in enterprise environments.
Responsibilities
- Manage delivery and support operations for Gen AI and AI, supervising AI initiatives considering user needs, new capabilities, and tech advancements.
- Oversee Gen AI, Classical AI, Data Science and Automation initiatives across Enterprise functions such as Supply Chain, Finance, Commercial, Customer Experience, Legal, HR and others.
- Manage and govern AI, GenAI models, AI Apps through experimentation and production lifecycles with MLOPs, LLMOps, AI Gateway and AI Observability tools.
- Accelerate Applied Gen AI Initiatives with creating a rapid iteration loop from idea to execution in line with responsible AI principles.
- Drive evaluation & observability first mindset bringing Gen AI reliability to the center stage.
- Strategize around creating a robust data flywheel ensuring a roadmap for continuous learning systems.
- Effectively use Gen AI to drive efficiency and optimization throughout the enterprise ecosystem.
Other
- A Master’s Degree or PhD in Computer Science, Engineering, Applied Mathematics or related field.
- Minimum 10 years of progressive experience in AI and Analytics, with a demonstrated track record of production grade enterprise-scale application development.
- Experience managing high-performing engineering teams and mentoring junior engineers in complex technical environments.
- Strong ability to translate complex AI concepts to business stakeholders and drive consensus across diverse teams.
- U.S. citizen, U.S. permanent resident, or have asylum or refugee status in the U.S.
