
10,000+ employees
Founded 1994
🛡️ Insurance
💼 Consulting
🏦 Banking
Insurance • Consulting • Banking
KeyBank is a full-service bank offering a wide range of financial services for individuals, small businesses, and large institutions. Services include personal and business banking, wealth management, loans, credit lines, mortgages, credit cards, and investment services. KeyBank also provides online and mobile banking tools to help customers manage their finances efficiently. With a focus on financial wellness, KeyBank offers resources to help customers understand banking basics, manage debts, and achieve their financial goals.
🔥 8 minutes ago
🇺🇸 United States – Remote
💵 $80k - $150k / year
⏰ Full Time
🟠 Senior
🧑💻 Full-stack Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 0%
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10,000+ employees
Founded 1994
🛡️ Insurance
💼 Consulting
🏦 Banking
Insurance • Consulting • Banking
KeyBank is a full-service bank offering a wide range of financial services for individuals, small businesses, and large institutions. Services include personal and business banking, wealth management, loans, credit lines, mortgages, credit cards, and investment services. KeyBank also provides online and mobile banking tools to help customers manage their finances efficiently. With a focus on financial wellness, KeyBank offers resources to help customers understand banking basics, manage debts, and achieve their financial goals.
• Design, train, and operationalize intelligent document-processing solutions • Turn unstructured and semi-structured documents into accurate, auditable, and actionable data products • Train, evaluate, and tune document extraction models for structured, semi-structured, and handwritten content • Perform entity and field extraction, confidence scoring, quality measurement, and model accuracy assessment • Implement document preprocessing, page-level validation, exception detection, and human-in-the-loop review patterns • Build Python-based data processing, automation, model integration, and reusable components • Develop cloud-native data pipelines using object storage, analytical databases, batch processing, and job orchestration • Implement configuration-driven validation to separate business rules from application code • Normalize and reconcile data, handle tolerances, and compare results against authoritative data sources • Apply encryption, decryption, sensitive-data controls, auditability, and secure cloud processing • Integrate APIs and systems for document ingestion, result publication, and downstream workflows • Select appropriate OCR, rules-based logic, machine learning, or generative AI solutions • Apply large language models to document understanding, unstructured content analysis, summarization, and reasoning use cases • Collaborate with business subject-matter experts to define fields, thresholds, exceptions, and acceptance criteria • Document model behavior, processing logic, decision outcomes, and operational procedures • Develop scalable, reusable solutions rather than one-off document automations • Support CI/CD, automated testing, environment promotion, infrastructure-as-code, monitoring, troubleshooting, and operational support
• 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 • Experience with Intelligent Document Processing (IDP), optical character recognition (OCR), and document classification • Experience training, evaluating, and tuning document extraction models for structured, semi-structured, and handwritten content • Experience with Python for data processing, automation, model integration, and reusable components • Experience with cloud-native data pipelines, object storage, analytical databases, batch processing, and job orchestration • Experience with encryption, decryption, sensitive-data controls, auditability, and secure cloud processing • Experience with APIs and system integration • 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 • 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 SQL-based analytical platforms, production data pipelines, batch and event-driven processing, workflow orchestration, retries, monitoring, and operational support • Experience with CI/CD, source control, automated testing, environment promotion, and infrastructure-as-code practices • Experience with observability and troubleshooting across model, application, data, and integration layers • Ability to translate document-review procedures into technical requirements and configurable validation rules • Ability to collaborate with business subject-matter experts to define fields, thresholds, exceptions, and acceptance criteria • Ability to document model behavior, processing logic, decision outcomes, and operational procedures • Ability to communicate complex AI and data-processing concepts to technical and non-technical stakeholders • This position is NOT eligible for employment visa sponsorship for non-U.S. citizens
• Base salary range of $80,000.00–$150,000.00 annually • Eligibility for incentive compensation, which may include production, commission, and/or discretionary incentives • Benefits for which this position is eligible (specific benefits list linked in posting) • Flexible options in circumstances where roles can be performed effectively in a mobile environment
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