Forward Deployed Engineer (FDE) – AI & Finance Data

Job Summary We are looking for Forward Deployed Engineers (FDEs) and technical specialists to form a dedicated POD supporting a large-scale Finance and Accounting data transformation initiative with a strong focus on AI enablement. The team will work closely with business and technology stakeholders to design, build, integrate, and deploy scalable data and AI solutions across data engineering, architecture, integration, semantic modeling, and knowledge management. Candidates should be highly hands-on, comfortable working across functions, and able to translate business requirements into production-ready solutions. The objective is to establish a trusted, scalable data foundation that enables advanced analytics, automation, GenAI, and emerging Agentic AI use cases.

Location: CT or MN. Must be local or relocate from DAY1

Domain: Healthcare : Finance Accountng Technology

Communication must be excellant

Duties

• Strong Finance and Accounting technology experience
• Experience delivering modern data platforms and data productsExpertise across cloud data technologies such as Snowflake, Databricks, and AzureStrong capabilities in semantic modeling, ontologies, and knowledge graphsExperience supporting AI, GenAI, LLM, or Agentic AI initiativesAbility to scale the team based on project requirementsStrong Agile delivery and architecture capabilitiesDevelopment of scalable financial data products and data pipelinesIntegration of ERP, financial, operational, and reporting data sourcesData modeling and development of standardized business metrics and KPIsDevelopment of semantic models and business definitionsCreation of metadata and data governance frameworksDevelopment of ontologies and knowledge modelsDesign and implementation of knowledge graph solutionsPreparation of data for AI, LLM, and Agentic AI applicationsDevelopment and support of cloud-based data platformsData quality, validation, reconciliation, and automated testingPerformance optimization and ongoing platform improvements
• Roles
• Data Architect – 1 Strong background in enterprise data architecture, cloud data platforms, data governance, and Finance/Accounting data.
• Data Engineers – 2–4 Experience building large-scale data pipelines and data products using technologies such as Python, SQL, Spark, Snowflake, Databricks, or similar platforms.
• Data Integration Engineers – 1–2 Experience integrating ERP and enterprise applications using APIs, event-driven architectures, batch and real-time integration patterns.
• Semantic / Analytics Engineers – 1–2 Experience with semantic modeling, business metrics, KPI definitions, business glossaries, and data models supporting analytics and AI.
• Ontology Engineers – 1–2 Experience developing ontologies, enterprise metadata models, RDF/OWL, and business-context models. Finance/Accounting experience is preferred.
• Knowledge Graph Engineers – 1–2 Experience with graph databases, relationship modeling, knowledge graph architecture, and integration with AI/LLM solutions.
• QA Engineers – 2 Experience testing data pipelines, data models, financial reconciliations, semantic models, and data quality frameworks.

Pay: $50.00 - $65.00 per hour

Experience:

• FDE: 6 years (Required)
• AI: 6 years (Required)
• LLM: 5 years (Required)

Work Location: Hybrid remote in Minneapolis, KS 67467