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United States
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Key Responsibilities
• Design and implement AI-powered automation workflows for archiving structured and unstructured data
• Integrate Claude (Anthropic API) to:
o Classify documents
o Extract metadata
o Apply retention and compliance logic
• Build and maintain solutions within Visual Studio / .NET or Python environments
• Develop prompt engineering strategies to improve accuracy and consistency in classification and tagging
• Create automation pipelines for ingestion, tagging, storage, and retrieval
• Collaborate with stakeholders to define archiving rules, taxonomy, and governance models
• Optimize performance, cost, and latency of LLM-driven processes
• Implement logging, monitoring, and validation to ensure reliability of outputs
• Document architecture, workflows, and best practices for handoff
Required Qualifications
• 5+ years of software engineering experience (backend or full-stack with strong backend focus)
• Hands-on experience working with LLMs (Claude, GPT, or similar) in production environments
• Strong development experience in Visual Studio (C#/.NET) and/or Python
• Experience building automation pipelines (APIs, batch processing, event-driven workflows)
• Solid understanding of:
o Data classification and document processing
o Prompt engineering and LLM evaluation techniques
• Experience integrating with REST APIs and cloud services (Azure preferred)
• Ability to work independently in a contract, outcome-driven environment
Preferred / Nice to Have
• Experience with records management, compliance, or archiving systems
• Familiarity with vector databases / embeddings for retrieval
• Exposure to RAG (Retrieval-Augmented Generation) patterns
• Experience with Azure AI Services or Azure OpenAI
• Background in building internal tools or enterprise automation platforms
Any Gradute
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