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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer - OCR / Text Extraction - **Company:** NetDocuments Software, Inc. - **Location:** United States - **Experience:** Expert - **Salary:** $170,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** AWS Textract, .NET Framework, Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, C Sharp (Programming Language), Software as a Service, Code Review, Information Systems, Document Management Systems, Distributed Systems, Enterprise Content Management, Information Extraction, Machine Learning, Enterprise Messaging Systems, Software Engineering, Data Streaming, Datadog, Data Logging, GitHub Copilot, Claude Code, Technical Debt, AI Coding Agents, Agentic-AI, Event Driven Architecture, Information Technology, Apache Kafka, Graphql, Functional Programming, Cloudwatch, Amazon Simple Queue Service (SQS), Microservices - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/staff-software-engineer-ocr-text-extraction--ac1f3061-7a48-496d-bb44-c27dd89ce052 ## About the Role Software Engineering, Document Management, Problem Solving Skills, Legal, Artificial Intelligence (AI), Enterprise Protection, Product Development, Team Player, Business Support, Distributed Computing, * Bachelor's degree or higher in Computer Science, Information Systems, or a related field, or equivalent experience. * 8+ years of professional software engineering experience delivering production systems at scale on cloud platforms. * Proven experience designing and owning distributed, event-driven systems that process high volumes in production. Please describe the scale of the systems you've built in your resume (for example, events or documents per hour or per day). * Experience leading technical direction for a team: making architecture decisions, setting standards, and growing other engineers. * U.S. citizenship is required for this role. * Expert proficiency in C#/.NET. * Expert proficiency designing event-driven, microservice-based systems, including failure handling, scaling and recovery. * Strong experience with Kafka or similar event streaming and messaging platforms. * Strong experience developing on cloud platforms, preferably AWS. * Strong experience with observability (logging, metrics, tracing, telemetry), preferably with Datadog. * Deep hands-on experience with OCR or document extraction technologies, such as Tesseract, Apryse, ABBYY, AWS Textract or Azure Document Intelligence. * Daily use of AI coding tools (for example, Claude Code or GitHub Copilot) across the development lifecycle, with sound judgment about reviewing and validating AI generated code. What Will Make You Stand Out * You know what it takes to ingest millions of documents an hour into a SaaS platform, and you've done it. * Experience building document management, enterprise content management, or high performance content extraction products. * Experience in the legal industry or in B2B SaaS for regulated industries. ## Description * Set technical direction for our document content extraction and transformation platform, establishing patterns for scalable, secure, and cost-efficient systems on AWS. * Design and own distributed, event-driven pipelines that process millions of documents an hour, including how they scale, how they fail, and how they recover. * Lead architectural decisions involving OCR technologies such as Tesseract and Apryse, and AI models for document understanding. * Drive improvements in throughput, reliability and performance, while controlling cost per document without affecting customer experience. * Make critical technical decisions that balance performance, security, cost and maintainability, with reasoning that stands up over time. Build & Operate * Build production services in C#/.NET using AWS (such as ECS, Lambda, S3 and SQS) and event streaming with Kafka. * Design resilient processing: retries, dead-letter handling, idempotency, backpressure, and graceful recovery. No silent failures. * Design and implement scalable APIs (REST, GraphQL) that power our product and enable third-party integrations. * Implement observability through logging, metrics, tracing and telemetry (Datadog, CloudWatch) to find and fix issues before customers notice. * Ensure security, compliance and confidentiality across all implementations. Legal documents are privileged, and our systems treat them that way. AI in the Product * Build the content pipelines that power semantic search: chunking, embeddings, vector indexing and evaluation, at the scale of millions of documents. * Measure and improve AI output quality with evaluation sets and metrics, while managing cost and latency in production. AI in How We Build * Lead the team's AI-assisted development practice, using AI agents such as Claude Code across specification, design, testing and implementation. * Set the standards for reviewing and approving AI-generated work so that speed never comes at the cost of quality. Ownership & Collaboration * Take full ownership of initiatives from concept through production and ongoing evolution. * Proactively identify and address technical debt before it affects the team or customers. * Partner with product management to turn requirements into technical solutions, and with Platform Services, Operations and other teams on shared infrastructure. * Mentor engineers at every level through design reviews, code reviews and documentation. * Build agreement on technical approaches, while having the authority to make the final call when needed. * Research and prove out new technologies through POCs that align with product strategy.