Senior AI Manager
Honeywell
Job Description
Job Description
As a Sr. AI Manager at Solstice Advanced Materials, you will be a part of IT team leading delivery of end-to-end AI initiatives across enterprise for GenAI & Classic AI/ML solutions while ensuring responsible AI and data engineering best practices. You will establish robust governance frameworks for AI applications through their entire lifecycle, leveraging MLOps, LLMOps, and observability tools to balance innovation with risk management. You will translate cutting-edge AI research into practical enterprise solutions while collaborating with technical and business teams to maximize AI's transformative impact on operational efficiency and strategic outcomes.
You will report to our Director IT of Gen AI, Data & Analytics Leader who oversees our enterprise data strategy, delivery and platform operations. This senior leadership role will drive enterprise-wide AI adoption, balancing innovation with responsible governance to deliver measurable business value across Solstice Advanced Materials. YOU MUST HAVE- 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.
- 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.
- Experience managing high-performing engineering teams and mentoring junior engineers in complex technical environments.
- AI & Advanced Analytics: 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.
- Preference alignment or Supervised Fine Tuning of LLMs.
- Large scale data preparation for training LLMs
- Experiment design or evaluation dataset creation for optimizing AI models.
- Predictive, forecasting or timeseries AI/ML models.
- AI/ML Framework such as Pytorch, Tensorflow or Scikit Learn.
- AI Agent/Workflow Framework such as Langchain, Langgraph, CrewAI, OpenAI SDK, Semantic Kernel.
- Strong ability to translate complex AI concepts to business stakeholders and drive consensus across diverse teams.
- Experience and domain knowledge of enterprise systems of records such as SAP for ERP, Salesforce for CRM and associated E2E processes etc.
- Background in enterprise domains such as Commercial, Finance, Supply Chain, Customer Experience and others.
- Prior publication record in top tier journals or conferences such as NeurIPS, AAAI, EMNLP, MICA or similar.
- Experience with AI Reliability, Trust and Safety, Responsible AI governance frameworks.
- Advanced experience with Infrastructure as Code (IaC) practices, Terraform/Bicep, Docker/Kubernetes, and cloud-native architecture in enterprise environments.
- Working knowledge of languages such as Spark, Scala, Rust, C#, Java or similar.
- Familiarity with IT Operations, ITIL practices and other service management frameworks.
- Ownership and Pride in your work and willingness to work in a diverse, cross-functional environment.
- 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. Guide and steer Corporate AI Risk Council balancing risk, compliance and speed for Gen AI adoption.
- 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. Collaborate with fellow Data Engineers and Analysts ensuring Data, Analytics and AI strategies share a common vision.
- Provide technical guidance on AI portfolio & strategy, effort sizing & estimation, as well as, build vs buy vs wait decisions.
- Effectively communicate by simplifying AI concepts for a diverse range of stakeholders.
- Collaborate with Enterprise Architecture, Security to help establish standards, frameworks and reference implementations for compound AI systems bringing clarity on classification aware data use and safe AI/Gen AI practices.
- Translate and align key research advancements in AI into actionable strategy for Solstice Advanced Materials, pushing the envelope with state of art, enterprise ready AI solutions.
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