Modernizing data infrastructure and building the next generation of data pipelines that power AI and machine learning initiatives, including cutting-edge Generative AI applications for The Hartford.
Requirements
- 12 years in data engineering, data management and building large-scale data ecosystems.
- 3+ years of AI/ML experience
- Mastery level data engineering and architecture skills, including deep expertise in data architecture patterns, data warehouse, data integration, data lakes, data domains, data products, business intelligence, and cloud technology capabilities.
- Technical expertise in LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval-Augmented Generation (RAG) architectures and vector database technologies (Vertex AI, Postgres, OpenSearch, Pinecone etc.).
- Strong experience with GCP, Vertex AI or AWS required.
- Experience in multi cloud environment.
- Experience in Lang chain, AI agents, Vertex AI and Google Agent ecosystem.
Responsibilities
- AI data Engineering lead responsible for Implementing end-to-end AI data pipelines bringing structured, semi-structured and unstructured data together supporting AI and Agentic solutions.
- Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery.
- Oversee the design, development, and maintenance of data pipelines, data warehouses, data lakes and reporting systems.
- Drive efficiency and Productivity: Identify and champion developer productivity improvements across the end-to-end data management lifecycle. This includes researching and implementing innovative solutions such as AI-driven auto-generation of data pipelines, advanced DevOps practices for data and automated data quality frameworks.
- Technology Evaluation & Adoption: Stay current with emerging trends in data engineering and AI/ML, design prototypes and conduct experiments, and recommend innovative tools and technologies to enhance data capabilities enabling business strategy.
- Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices.
- Partners with Technology, Data, AI Platform, ML Ops and Architecture teams to influence technology, data, platform and tooling strategy.
Other
- 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).
- 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.
- Proven strategic and innovative thinker with a track record of enabling transformative data capabilities.
- Exceptional presentation and verbal/written communication skills; must be able to communicate effectively at all levels across the organization.
- Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working.
