Principal AI Data Engineer

As a Principal Data Engineer here at Honeywell you will play a crucial role in designing and implementing advanced data solutions for AI solutions that drive business insights enhance decision-making processes and empower AI solutions. Your expertise will help in critical data science development activities across all AI modalities (classic Gen and agentic) and data types (structured and unstructured).

You will report directly to our AI Director and youll work out of our Phoenix AZ location on a Hybrid work schedule.

In this role you will impact the organization by leveraging your technical skills to develop innovative data solutions that support strategic initiatives and improve operational efficiency.

At Honeywell our people leaders play a critical role in developing and supporting our employees to help them perform at their best and drive change across the company. Help to build a strong diverse team by recruiting talent identifying and developing successors driving retention and engagement and fostering an inclusive culture.

• Support endtoend data needs forall AI modalities including classic ML GenAI/LLMs and agentic AI systems.
• Build robust scalable data pipelines forstructured semistructured and unstructured data including text documents images audio video and logs.
• Develop feature engineering pipelines for classic ML including feature extraction transformation and feature store management.
• Build and optimizeGenAI and LLM data pipelines including embedding generation vectorization chunking metadata extraction and document enrichment for RAG and context retrieval.
• Develop data ingestion and orchestration workflows that supportagentic AI including memory stores event-driven pipelines tool-use data flows and real-time retrieval services.
• Design and implement advanced data solutions usingAWS (S3 Glue Lambda EMR Kinesis) Databricks (Spark Delta Lake Vector Search) and Dataikuto enable intelligent systems at scale.
• Implement data governance quality lineage monitoring and observability to support high-performance trustworthy AI.
• Partner with data scientists ML engineers and AI product teams to deliver datasets for model development finetuning evaluation and production inference.
• Optimize pipelines for latency cost reliability and throughput ensuring AI systemsfrom batch ML to real-time agentshave the data they need.

• Bachelors degree in a technical field (CS Engineering Math or related).
• Experience supporting AI at scale acrossclassic ML GenAI/LLM and agentic AI systems.
• Experience with vector databases and semantic search (Databricks Vector Search Pinecone FAISS Milvus OpenSearch).
• Familiarity withLLM and GenAI data preparation including:
  • Text processing
  • Tokenization
  • Chunking strategies
  • Prompt/context formatting
• Experience with unstructured data technologies (OCR NLP pipelines computer vision data processing).
• Hands-on experience with Dataiku for automation workflow orchestration and AI project management.
• Knowledge of MLOps tooling: MLflow Delta Lake experiment tracking CI/CD for ML.
• Understanding ofagentic AI system patterns such as memory architectures tool APIs event-driven workflows and reasoning chain data requirements.
• Strong analytical mindset attention to detail and commitment to high data quality.
• Ability to thrive in a fast-paced evolving AI environment and collaborate across cross-functional teams.

BENEFITS OF WORKING FOR HONEYWELL

In addition to a competitive salary leading-edge work and developing solutions side-by-side with dedicated experts in their fields Honeywell employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical Dental Vision and Life Insurance; Short-Term and Long-Term Disability; 401(k) match Flexible Spending Accounts Health Savings Accounts EAP and Educational Assistance; Parental Leave Paid Time Off (for vacation personal business sick time and parental leave) and 12 Paid Holidays. For more information visit: click here

The application period for the job is estimated to be 40 days from the job posting date; however this may be shortened or extended depending on business needs and the availability of qualified candidates.

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