Lead AI/ML Engineer Enterprise Finance || Minneapolis MN

• Design and develop scalable enterprise AI/ML and Generative AI solutions.
• Build production-grade LLM applications, RAG pipelines, AI agents, classification models, summarization workflows, and decision-support systems.
• Design prompt engineering, prompt orchestration, grounding, tool-calling, guardrails, and fallback mechanisms.
• Develop and optimize agentic AI workflows, including multi-step reasoning and tool/API integrations.
• Establish AI evaluation frameworks, test datasets, scoring methodologies, and performance benchmarks.
• Evaluate and optimize AI systems for accuracy, relevance, hallucination risk, latency, reliability, and cost.
• Integrate AI applications with enterprise APIs, data platforms, vector databases, and governed data sources.
• Perform failure-mode analysis and continuously improve production AI systems.
• Implement AI observability, monitoring, evaluation, and model/drift monitoring practices.
• Ensure solutions meet enterprise requirements around Responsible AI, security, privacy, compliance, and governance.
• Collaborate with Data Engineering, Architecture, Security, Quality Engineering, and business stakeholders.

The ideal candidate will combine strong AI/ML engineering expertise with production software engineering skills and experience taking AI solutions from architecture and development through evaluation, deployment, monitoring, and governance. Experience supporting Finance, FP&A, Accounting, Treasury, or Tax functions is highly preferred., * Strong experience in AI/ML Engineering or Software Engineering.

• Hands-on production experience with Generative AI and LLM-based applications.
• Strong experience with RAG architectures and retrieval/grounding techniques.
• Hands-on experience building AI agents / Agentic AI solutions.
• Strong knowledge of prompt engineering and LLM orchestration.
• Experience integrating LLMs with APIs, enterprise applications, and data sources.
• Experience with model/LLM evaluation frameworks, guardrails, and hallucination mitigation.
• Strong understanding of cloud-native architectures, APIs, data platforms, and scalable distributed applications.
• Knowledge of Responsible AI, security, privacy, compliance, and AI governance.
• Strong communication skills and ability to work with both technical and business stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent relevant experience.

Preferred Skills

• 1 2+ years of hands-on Agentic AI development/deployment experience.
• Experience with vector databases, semantic search, embeddings, knowledge retrieval, and AI observability.
• Experience taking enterprise AI products from architecture/design through production deployment and support.
• Experience working with Finance, FP&A, Accounting, Treasury, Tax, or related enterprise finance functions.