Sr. Full Stack Engineer

• Intelligent Document Processing (IDP), optical character recognition (OCR), and document classification 

• Training, evaluating, and tuning document extraction models for structured, semi-structured, and handwritten content 

• Entity and field extraction, confidence scoring, quality metrics, and model accuracy assessment 

• Document preprocessing, page-level validation, exception detection, and human-in-the-loop review patterns 

• Python development for data processing, automation, model integration, and reusable components 

• Cloud-native data pipelines using object storage, analytical databases, batch processing, and job orchestration 

• Configuration-driven validation using YAML or similar formats to separate business rules from application code 

• Data normalization, reconciliation, tolerance handling, and comparison against authoritative data sources 

• Encryption, decryption, sensitive-data controls, auditability, and secure cloud processing 

• API and system integration for ingesting documents, publishing results, and supporting downstream workflows 

• Practical experience with document AI platforms or comparable machine learning services 

• Understanding of supervised model training, labeling strategies, evaluation datasets, confidence thresholds, and error analysis 

• Ability to identify when OCR, rules-based logic, machine learning, or generative AI is the appropriate solution 

• Experience applying large language models to document understanding, unstructured content analysis, summarization, or reasoning use cases 

• Knowledge of responsible AI practices, including explainability, traceability, quality controls, and review escalation 

• Experience with cloud object storage, SQL-based analytical platforms, and production data pipelines 

• Batch and event-driven processing patterns, workflow orchestration, retries, monitoring, and operational support 

• Data modeling for extracted values, confidence scores, validation results, and processing history 

• CI/CD, source control, automated testing, environment promotion, and infrastructure-as-code practices 

• Observability and troubleshooting across model, application, data, and integration layers 

• Ability to translate document-review procedures into clear technical requirements and configurable validation rules 

• Collaboration with business subject-matter experts to define fields, thresholds, exceptions, and acceptance criteria 

• Clear documentation of model behavior, processing logic, decision outcomes, and operational procedures 

• Ability to communicate complex AI and data-processing concepts to technical and non-technical stakeholders 

• Focus on scalable, reusable solutions rather than one-off document automations 

• Bachelor's Degree in Information Systems, Computer Science, Data Analytics, or related technical field

• Hands-on experience delivering document-processing or information-extraction solutions in a regulated industry 

• Experience with sensitive or confidential information and enterprise security controls 

• Familiarity with cloud-based machine learning and data platforms 

• Knowledge of financial-services, legal, healthcare, insurance, or other document-intensive workflows 

• Experience designing exception-based workflows that reduce manual review while preserving quality and control 

This position is NOT eligible for employment visa sponsorship for non-U.S. citizens.

COMPENSATION AND BENEFITS

Please click here for a list of benefits for which this position is eligible.

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