Senior Consultant CPM (Forward Deployed Engineer)

Accordion•Atlanta, GA

8d•$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 transform how organizations interact with their Enterprise Performance Management (EPM) and Corporate Performance Management (CPM) systems. Rather than implementing the platforms themselves, this role focuses on creating intelligent solutions—such as FP&A variance analysis agents, close reporting agents, forecasting co-pilots, and automated data reconciliation workflows—that sit on top of existing financial systems and dramatically accelerate the speed and quality of financial decision-making. The FDE will work at the intersection of applied AI, financial domain expertise, and client delivery—understanding the nuances of each client’s financial architecture, identifying high-value automation opportunities, and shipping production-grade AI agents that become embedded in the client’s day-to-day finance operations.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Finance, or a related field.
3+ years of software engineering experience, with at least 1 year focused on building applications powered by large language models, AI agents, or intelligent automation.
Strong proficiency in Python and experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, Anthropic API, OpenAI API) and related tooling (vector databases, embedding models, 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 with the ability to work directly with CFOs, controllers, and FP&A leaders—translating their needs into technical solutions and demonstrating value through rapid iteration.
Willingness to travel to client sites as needed (up to 50–80%, depending on engagement).

Nice To Haves

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

Responsibilities

Design, build, and deploy AI agents tailored to client-specific financial workflows, including variance analysis agents that automatically surface and explain P&L and balance sheet movements, close reporting agents that generate narrative commentary and executive summaries, and forecasting co-pilots that assist FP&A teams with scenario modeling and assumption validation.
Build integrations between AI agents and existing EPM/CPM platforms (e.g., Oracle EPM Cloud, OneStream, Anaplan, Planful, Workday Adaptive Planning) to read from and write back to the client’s system of record.
Develop automated data reconciliation and validation workflows that reduce manual effort during period-end close, intercompany eliminations, and management reporting cycles.
Implement retrieval-augmented generation (RAG) pipelines, tool-use patterns, and multi-step agent architectures that ground AI outputs in the client’s actual financial data and business context.
Embed with client finance, FP&A, and accounting teams to deeply understand their existing EPM/CPM environment, data flows, reporting cadences, and pain points.
Identify and prioritize high-impact opportunities where AI agents and automation can eliminate manual, repetitive work—particularly in variance commentary, flux analysis, board reporting, cash flow forecasting, and data quality assurance.
Translate business requirements into technical solution architectures, defining agent capabilities, data source integrations, guardrails, and success metrics in collaboration with client stakeholders.
Manage the full lifecycle of agent development on-site—from rapid prototyping and stakeholder demos through iteration, testing, deployment, and post-launch monitoring.
Contribute to Accordion’s reusable agent framework and shared component library, abstracting patterns from client engagements into configurable, scalable building blocks for future deployments.
Stay current on advances in large language models, agent frameworks (e.g., LangChain, LangGraph, CrewAI, Anthropic tool use), and emerging best practices for building reliable, auditable AI systems in financial contexts.
Establish and enforce quality standards for AI outputs in financial workflows, including accuracy validation, hallucination mitigation, audit trail generation, and appropriate human-in-the-loop checkpoints.
Document solution architectures, integration patterns, and deployment playbooks to accelerate future client engagements and enable knowledge transfer across the team.