Lead AI/ML Engineer – Enterprise Finance

Sygna Solutions; Minneapolis (MN); On-site; USD 140,000 - 190,000; Full time

Job summary

Sygna Solutions is seeking a Lead AI/ML Engineer to design, build, and operationalize AI capabilities across the Finance organization. You will lead LLM workflows, RAG apps, agents, and governance while partnering with Data Engineering and Security teams.

The role emphasizes scalable, trusted AI with enterprise-grade standards and observability, enabling decision-support across finance functions. Remote options are not specified.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• 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.

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.

Skills

Software engineering

Machine learning

AI engineering

LLM applications

Prompt engineering

RAG architectures

AI governance

Cloud-native architectures

APIs

Security and compliance

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Vector databases

Semantic search

Knowledge retrieval systems

Model evaluation tools

Job description

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.