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Senior AI Data Engineer - Hybrid

Job in Columbus, Franklin County, Ohio, 43224, USA
Listing for: The Hartford
Full Time, Part Time position
Listed on 2026-07-10
Job specializations:
  • Software Development
    Data Engineering, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 135040 - 202560 USD Yearly USD 135040.00 202560.00 YEAR
Job Description & How to Apply Below
Position: Senior Staff AI Data Engineer - Hybrid

Sr Staff Data Engineer - GE07DE

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

Join our team as a Senior Staff AI Data Engineer and lead the charge in developing cutting‑edge AI solutions and data engineering strategies. Embrace our core values of innovation, collaboration, and excellence as you unlock unparalleled growth opportunities in the dynamic field of AI and data engineering. Shape the future of technology with us! Apply now to be part of our innovative journey and make a significant impact!

This role will have a hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).

Primary

Job Responsibilities
  • Lead the implementation of AI data pipelines integrating structured, semi‑structured, and unstructured data to support AI and agentic solutions, including preprocessing techniques such as extraction, chunking, embedding, and grounding (e.g., RAG, retrieval frameworks)
  • Develop AI‑driven data systems that enhance data capabilities while ensuring adherence to industry best practices
  • Implement and optimize Retrieval‑Augmented Generation (RAG) architectures and integrate them with enterprise data platforms
  • Design, build, and optimize scalable batch and streaming data pipelines with a focus on performance, resiliency, and operational efficiency
  • Develop and maintain real‑time data streaming pipelines using technologies such as Snowpipe
  • Develop data domains and data products to support reporting, analytics, AI/ML, and data science use cases
  • Ensure the reliability, availability, and scalability of data pipelines through monitoring, alerting, and incident management
  • Implement reliability engineering best practices, including fault tolerance, redundancy, and disaster recovery
  • Drive engineering discipline across data platforms, including observability, data quality, lineage, and governance
  • Collaborate with Dev Ops and infrastructure teams to enable seamless deployment and operation of data systems
  • Partner with cross‑functional teams to integrate data and AI solutions into business processes and enterprise systems
  • Provide architectural leadership in partnership with Data Architects, including defining technical standards and influencing enterprise‑wide practices
  • Develop and integrate graph database solutions to support complex data relationships within AI systems
  • Apply GenAI approaches to insurance‑specific data use cases and challenges
  • Lead the development of AI‑ready data foundations that support scalable, production‑grade solutions
  • Ensure data platforms remain resilient, governed, and cost‑efficient, aligned with enterprise cloud and data strategies
  • Mentor junior engineers and contribute to communities of practice, promoting best practices, reusable patterns, and engineering standards
  • Stay current with advancements in GenAI and apply relevant technologies and methodologies to platform evolution
Skills
  • Strong technical expertise in AI‑driven data solutions leveraging modern cloud platforms
  • Deep expertise in core data engineering, including advanced SQL, data modeling, and query performance tuning
  • Strong experience in ETL/ELT architecture, orchestration frameworks, and pipeline optimization
  • Experience working across teams with strong communication and stakeholder management skills
  • Proven ability to mentor and develop AI and data engineering talent
  • Knowledge of emerging AI and data engineering design patterns
  • Strong planning, organization, and execution capabilities
  • Ability to lead in a lean, agile, and fast‑paced environment, leveraging Scaled Agile practices
  • Strong analytical and problem‑solving skills with the ability to translate business requirements into technical solutions
  • Demonstrated leadership capability to own architecture decisions and drive cross‑team alignment
  • Effective collaboration, decision‑making, and relationship‑building skills
  • Strong interpersonal skills with the…
Position Requirements
10+ Years work experience
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