Sr Knowledge Engineer, Text Factory

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.   

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working at The Hartford means having the opportunity to grow your career while helping build real, enterprise grade AI capabilities.

The Hartford is seeking a Sr Knowledge Engineer to join our AI Enablement Text Factory organization.  This role is ideal for a mid to-senior career data engineer who enjoys applying their technical linguistic expertise to power scalable, enterprise grade products.

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office should maintain their current work arrangement with the expectation of coming into the office as business needs arise.
 
Key Responsibilities

• Drive the end to end migration of a legacy, rules based text processing platform to a modern, Python based natural language processing (NLP) architecture, improving scalability, maintainability, and long term extensibility.
• Modernize legacy extraction logic.  Analyze existing grammar, pattern rules, and linguistic logic from legacy systems and refactor them into contemporary NLP pipelines using industry standard libraries and frameworks.
• Design and implement context aware extraction. Build, test, and maintain high precision context extraction logic to identify entities, attributes, events, and relationships that support new product development and advanced analytics use cases
• Apply ontologies and taxonomies to text understanding.  Develop, extend, and apply domain ontologies and taxonomies to standardize language interpretation, support semantic consistency, and improve the accuracy and explainability of extraction results.

Experience & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience) is required.
• 7+ years of experience in data analysis, transformation, and development, with a strong specialization in Natural Language Processing in the insurance industry.
• 5+ years of strong proficiency in SQL and Python
• Strong background in natural language processing and text analytics, with hands on experience building rule based and hybrid (rules + ML/AI) extraction solutions.
• Applied experience designing and using ontologies and taxonomies to model domain concepts, normalize language, and support semantic interpretation of unstructured text.
• Deep expertise in context aware information extraction, including pattern matching, dependency based rules, negation handling, section awareness, and linguistic feature engineering.
• Proficiency in Python software development, including building production ready libraries, writing maintainable code, and debugging complex text processing pipelines.
• Experience working with large volumes of unstructured or semi structured text, such as documents, notes, forms, or free text fields.
• Ability to align extraction outputs to canonical domain models, controlled vocabularies, and taxonomy structures.
• Familiarity with extraction evaluation and tuning, including precision/recall measurement, error analysis, and iterative rule optimization.
• Understanding of data integration and pipeline concepts, including how extracted features are consumed by downstream analytics, ML models, or enterprise applications.
• Ability to translate evolving business and product requirements into precise, testable extraction logic.
• Experience supporting new product development, where requirements are iterative and domain models, terminology, and extraction strategies evolve over time.
• Strong communication skills to explain NLP behavior, limitations, and tradeoffs to both technical and non technical stakeholders.

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:

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