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Senior AI Engineer

Accordion
CompanyAccordion
CategoryEngineering
LocationAtlanta; Boston; Charlotte; Chicago; Dallas; Los Angeles; New York; San Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted17 Mar 2026
Last verified3 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
Company Overview We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation. If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment. Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark.  Data & Analytics Accordion's Data & Analytics (D&A) team offers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges. We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics. This role can be based in any of our US office locations and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location. This position is not eligible for immigration sponsorship. Accordion Intelligence Lab The AI Lab is composed of leading software and AI engineers, designing agentic-AI solutions ahead of the market. Our group builds and operationalizes the AI systems that power Accordion’s consulting capabilities, from agentic architectures and RAG pipelines to evaluation frameworks and production observability. The Lab works closely with practice leaders to translate research findings into scalable, reliable tools that advance Accordion’s AI-driven value creation work for PE clients and their portfolio companies. About the Role We’re looking for experienced AI Engineers to join new AI-augmented delivery pods: purpose-built teams that combine AI engineering, data science, and product management to transform how PE-backed companies run finance and operations. In this role, you will design and build the AI systems that power client engagements: agentic workflows, RAG pipelines, evaluation frameworks, and production-grade tools that operate in real PE environments. You’ll work directly with clients and cross-functional pod teammates from day one, and you will be expected to ship fast, defend your decisions, and continuously raise the bar on what AI-assisted delivery looks like. This is a highly technical, hands-on role. We move at sprint pace—not quarter pace. If you want to move quickly, own outcomes end-to-end, and build things that matter in finance, this is the role. What You’ll Do Design and build multi-agent systems and RAG pipelines that automate financial workflows for PE-backed portfolio companies Own the full stack from prompt engineering and tool design through deployment and monitoring Practice eval-driven development: define how success is measured before you build Translate ambiguous client problems into engineering requirements and deliver results in compressed timeframes Present and defend architectural decisions to technical and non-technical audiences—including CFOs and PE operators Build observability and evaluation infrastructure to continuously improve production AI system quality Travel to client site as needed Success in the First 6 Months Work with like-mined AI engineers to ship at least one end-to-end agentic solution in a client engagement, from scoping through production Establish evaluation infrastructure for your pod’s systems so that quality is measurable and regressions are caught early Demonstrate materially faster delivery cycles because of how you use AI tools��
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