We’re seeking an experienced AI/ML Engineer to design and implement intelligent exception resolution capabilities within our financial reconciliation platform. You’ll integrate advanced language models (Claude/OpenAI) into our core pipeline, crafting sophisticated prompts that transform complex reconciliation exceptions into clear, auditable resolution suggestions. This role is critical to delivering AI-powered insights that help financial teams resolve discrepancies faster and with greater confidence.

What You’ll Do

• Design and optimize prompts that accurately interpret flagged reconciliation exceptions and generate structured, actionable resolution suggestions with confidence scoring
• Integrate LLM APIs (Anthropic Claude, OpenAI) into the exception resolution layer using Python, the Anthropic SDK, and async API patterns for production-grade reliability
• Develop human-in-the-loop workflows that balance automation with human oversight, ensuring financial accuracy and auditability at every step
• Build robust API integration code that handles edge cases, rate limiting, token management, and graceful error recovery in a financial context
• Collaborate with backend developers to embed AI outputs cleanly into the reconciliation pipeline and ensure seamless data flow into final reports
• Implement LLM evaluation and benchmarking frameworks to measure prompt effectiveness, accuracy, and consistency across diverse exception types
• Document prompt strategies and model behavior to enable knowledge sharing and continuous improvement across the engineering team
• Monitor and iterate on model performance, refining prompts and integration logic based on real-world exception data and user feedback

What We’re Looking For

Required Qualifications:

• 3+ years of professional software engineering experience, with at least 2+ years working directly with LLM APIs (Anthropic, OpenAI, or similar)
• Strong proficiency in Python, including hands-on experience with the Anthropic SDK and async API calls
• Demonstrated expertise in prompt engineering, particularly for structured outputs and domain-specific tasks
• Solid understanding of confidence scoring, uncertainty quantification, and human-in-the-loop AI workflows
• Experience writing clean, maintainable API integration code with attention to edge cases and error handling
• Ability to work independently and communicate effectively with cross-functional teams
• Familiarity with financial systems, reconciliation processes, or similar regulated domains is a plus

Technical Skills:

• Backend development and ETL middleware concepts
• Agent orchestration and agentic AI patterns
• LLM evaluation and benchmarking methodologies
• Version control (Git) and collaborative development practices

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