Sygna Solutions
Lead AI/ML Engineer – Enterprise Finance
Remote•United States•Contract
About the Job
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.