Lead AI/ML Engineer – Enterprise Finance

Lead AI/ML Engineer, Enterprise Finance

We are seeking a Lead AI/ML Engineer to design, build, and operationalize AI capabilities that drive decision-making, productivity, and innovation across the Finance organization.

In this role, you will lead the development of AI-powered solutions including large language model (LLM) applications, retrieval-augmented generation (RAG), intelligent agents, classification models, summarization workflows, and decision-support tools. You will work closely with Finance, Data Engineering, Architecture, Security, and Responsible AI teams to deliver trusted, scalable, and governed AI solutions. The role aligns with enterprise AI/ML engineering practices and AI productization standards

Key Responsibilities:

- Design AI solution architectures aligned with business objectives, risk tolerance, and governance requirements. - Build and deploy LLM workflows, prompt orchestration chains, agent-based solutions, RAG applications, model integrations, classification models, and decision-support capabilities. - Develop prompt strategies, grounding approaches, tool-calling patterns, guardrails, and fallback mechanisms to improve solution quality and reliability. - Partner with Data Engineering teams to ensure access to trusted, governed, and high-quality data sources. - Establish evaluation frameworks, test datasets, scoring rubrics, and model-performance benchmarks. - Monitor and optimize output quality, relevance, accuracy, consistency, latency, cost efficiency, and hallucination risk. - Conduct failure-mode analysis and implement continuous improvements to AI systems. - Collaborate with Quality Engineering, Responsible AI, Security, Privacy, Compliance, and Enterprise Architecture teams. - Document AI solution behavior, limitations, controls, and operational monitoring requirements. - Support production readiness through observability, monitoring, model evaluation, and drift detection practices.

Required Qualifications:

- Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field; equivalent experience considered. - Significant experience in software engineering, machine learning, or AI engineering. - Hands-on experience building and deploying generative AI and LLM-based applications in production environments. - Experience with prompt engineering, RAG architectures, AI agents, model evaluation, and operational AI governance. - Strong understanding of cloud-native architectures, APIs, data platforms, and scalable software systems. - Knowledge of Responsible AI, security, privacy, and compliance practices. - Proven ability to work effectively with technical and business stakeholders.

Preferred Qualifications:

- Experience supporting Finance, FP&A, Accounting, Treasury, Tax, or other enterprise finance functions. - 1-2+ years in developing and deploying agentic AI solutions. - Familiarity with AI observability, model monitoring, vector databases, semantic search, and knowledge retrieval systems. - Experience leading enterprise AI products from design through production support.