Senior Consultant CPM (Forward Deployed Engineer)

Accordion•Atlanta, GA

5d•$95,000 - $140,000•Hybrid

About The Position

Accordion is seeking a Forward Deployed Engineer (FDE) to embed directly with client finance teams and build AI-powered agents and automated workflows that improve how organizations use existing Enterprise Performance Management (EPM) and Corporate Performance Management (CPM) systems. The role focuses on intelligent solutions built on top of clients’ financial systems, including variance analysis agents, close reporting agents, forecasting co-pilots, and automated data reconciliation workflows. The FDE works at the intersection of applied AI, financial domain expertise, and client delivery. The role involves understanding each client’s financial architecture, identifying valuable automation opportunities, and deploying production-grade AI agents for everyday finance operations. The position is available from any US office location and is hybrid, with the flexibility to work remotely two days per week; candidates should ideally be local to their desired location. The role requires travel to client sites as needed, potentially up to 50–80% depending on the engagement, and is not eligible for immigration sponsorship.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Finance, or a related field.
At least 3 years of software engineering experience, including at least 1 year building applications powered by large language models, AI agents, or intelligent automation.
Strong proficiency in Python and experience with LLM orchestration frameworks and related tools, such as LangChain, LangGraph, Anthropic API, OpenAI API, vector databases, embedding models, and prompt engineering.
Working knowledge of financial processes, including budgeting, forecasting, financial consolidation, close management, variance analysis, and management reporting.
Solid SQL skills and experience integrating with APIs, data warehouses, ERPs, and financial systems to source and transform data for AI workflows.
Excellent communication skills and ability to work directly with CFOs, controllers, and FP&A leaders, translate needs into technical solutions, and demonstrate value through rapid iteration.
Willingness to travel to client sites as needed, up to 50–80% depending on the engagement.

Nice To Haves

Understanding of financial planning and reporting systems such as Oracle EPM Cloud, OneStream, Anaplan, Planful, or Workday Adaptive Planning.
Experience in consulting or professional services.
Familiarity with ERP systems such as NetSuite, SAP, Oracle EBS, or Microsoft Dynamics, and with financial data flows from transactional systems into EPM/CPM platforms.
Experience building production AI systems with guardrails for regulated or audit-sensitive environments, including explainability, traceability, and human-in-the-loop review patterns.
Cloud infrastructure experience with AWS, Azure, or GCP and comfort deploying and monitoring agent-based applications in production.
Background in financial data modeling, multidimensional databases, or business intelligence tooling.

Responsibilities

Design, build, and deploy AI agents tailored to client financial workflows, including variance analysis, close reporting, and forecasting.
Build integrations between AI agents and existing EPM/CPM platforms to read from and write to clients’ systems of record.
Develop automated data reconciliation and validation workflows for period-end close, intercompany eliminations, and management reporting.
Implement retrieval-augmented generation pipelines, tool-use patterns, and multi-step agent architectures grounded in client financial data and business context.
Work with client finance, FP&A, and accounting teams to understand their EPM/CPM environments, data flows, reporting cadences, and pain points.
Identify and prioritize opportunities for AI and automation, including variance commentary, flux analysis, board reporting, cash flow forecasting, and data quality assurance.
Translate business requirements into technical architectures, defining agent capabilities, integrations, guardrails, and success metrics with client stakeholders.
Manage agent development from prototyping and stakeholder demonstrations through iteration, testing, deployment, and post-launch monitoring.
Contribute reusable patterns and components to Accordion’s agent framework and shared component library.
Stay current on large language models, agent frameworks, and best practices for reliable, auditable AI in financial contexts.
Establish quality standards for financial AI outputs, including accuracy validation, hallucination mitigation, audit trails, and human-in-the-loop checkpoints.
Document solution architectures, integration patterns, and deployment playbooks to support future engagements and team knowledge transfer.