Lead Gen AI Data Engineer

Posted 2 Days Ago
4 Locations
In-Office
135K-203K Annually
Senior level
Fintech • Payments • Financial Services
The Role
The Sr GenAI Data Engineer will design and implement AI-driven data solutions, improving data capabilities and integrating with enterprise systems while mentoring junior team members.
Summary Generated by Built In
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 Sr GenAI 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 (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

Key Responsibilities:

Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices. Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure. Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions. Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems. Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar. Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc. Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management. Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies. Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems. Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns. Apply AI solutions to insurance-specific data use cases and challenges. Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.

Required Skills & Experience:

  • 8+ years’ Strong hands-on experience programming skills in Python.
  • 7+ years of data engineering Strong hands-on experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark.
  • 3+ years of data engineering experience focused on supporting Generative AI technologies.
  • 2+ years Strong hands-on experience implementing production ready enterprise grade GenAI data solutions.
  • 3+ years’ experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.
  • 3+ years’ Experience of vector databases and graph databases, including implementation and optimization.
  • 3+ years’ Experience in processing and leveraging unstructured data for GenAI applications.
  • 3+ years’ Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph).
  • 3+ years’ Experience with building AI pipelines that bring together structured, semi-structured and unstructured data. This includes pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and getting the data ready for Models and Agentic solutions.
     

Nice to Have:

  • Experience with prompt engineering techniques for large language models.
  • Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform.
  • Experience in multi cloud hybrid AI solutions.
  • AI Certifications Experience in P&C or Employee Benefits industry Knowledge of natural language processing (NLP) and computer vision technologies.
  • Contributions to open-source AI projects or research publications in the field of Generative AI.

Candidate 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.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$135,040 - $202,560

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits

Top Skills

AWS
Aws Lambda
Azure
Big Data
Ci/Cd
Ec2
Elt
ETL
GCP
Langchain
Langgraph
NoSQL
Python
S3
Snowflake
Spark
SQL
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The Company
HQ: Hartford, Connecticut
20,002 Employees
Year Founded: 1810

What We Do

Human achievement is at the heart of what we do. We put our belief into action by not only ensuring individuals and businesses are well protected, but by going even further – making an impact in ways that go beyond an insurance policy

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