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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Staff AI Data Engineer - Hybrid - **Company:** The Hartford - **Location:** Columbus, OH, United States - **Experience:** Expert - **Salary:** $135,040.0 - $202,560.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Encodings, Computer Programming, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Systems, Software Design Patterns, DevOps, Disaster Recovery, Fault Tolerance, Graph Database, Python (Programming Language), Meta-Data Management, Open Source Technology, Reliability Engineering, SQL Databases, Data Streaming, Unstructured Data, Google Cloud, Cloud Platform System, Sql Optimization, Snowflake, Multi-Cloud, Generative AI, Kubernetes, Information Technology, Data Management, Data Pipelines - **Published:** June 12, 2026 - **Apply:** https://www.juju.com/job/00000000g7qqq7 ## About the Role + 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 ability to provide **thought leadership** in a dynamic environment Qualifications + Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. + Bachelor's degree in Computer Science, Artificial Intelligence, or a related field + 8+ years of data engineering experience with deep expertise in **SQL, data modeling, and large-scale data processing systems** + Proven experience designing and optimizing **ETL/ELT pipelines and orchestration frameworks** in enterprise environments + Experience supporting **Generative AI data engineering use cases** + Hands-on experience implementing **production-ready, enterprise-grade GenAI data solutions** + Experience implementing **RAG pipelines** , including retrieval, chunking, embedding, and grounding techniques + Experience operationalizing **GenAI pipelines in production environments** + Hands-on experience with **cloud ecosystems** (AWS, GCP, Azure, Snowflake) and Python-based data engineering stacks + Proven ability to deliver **resilient, governed, and cost-efficient data platforms at scale** + Experience with **vector databases and graph databases** , including design and optimization + Experience working with **unstructured data for GenAI applications** + Experience implementing **data governance practices** , including data quality, lineage, and data cataloging at scale + Proficiency in building AI data pipelines that integrate structured and unstructured data with preprocessing techniques + Strong programming skills in **Python** + Strong communication skills and ability to explain technical concepts to a broad set of stakeholders Preferred Qualifications + Experience designing **multi-cloud or hybrid AI data solutions** + AI-related certifications + Experience in the **P&C insurance industry** + Contributions to open-source AI projects or research in Generative AI ## Description 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 DevOps 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 ## Related Videos - [AI PowerPlay: Building High-Impact Teams & Transformative Solutions](https://www.wearedevelopers.com/videos/1005-ai-powerplay-building-high-impact-teams-transformative-solutions) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) ## Related Articles - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Got AI ideas but no money? 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