Senior Software Engineer

About the role

Accordion is private equity's value creation partner, sitting 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. Backed by premier private equity firms and headquartered in New York with 11 offices globally, we are a high-growth, entrepreneurial firm of 1,600+ finance & technology experts.

The Data & Analytics (D&A) team offers cutting-edge, intelligent solutions to a global clientele across Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics, leveraging domain knowledge, sophisticated technology tools, and deep analytics capabilities.

The AI Lab builds and operationalizes the AI systems that power Accordion's consulting capabilities—from agentic architectures and RAG pipelines to evaluation frameworks and production observability. New hires join AI-augmented delivery pods alongside AI engineering, data, and product teammates, initially integrating with the broader Lab team before moving into a specialized pod.

This posting covers two levels: Associate Software Engineer and Senior Software Engineer. We're looking for engineers who want to build real agentic systems, not tinker with demos. You'll work under the direction of Staff-level engineers on live client engagements—writing agent logic, RAG pipelines, eval harnesses—and grow steadily toward owning a workstream. This is a highly technical, hands-on role in a high-velocity, client-facing environment: sprints are short, client expectations are high, and the work is real from week one. You'll ship fast, learn quickly, and raise your own bar on what AI-assisted delivery looks like.

This role can be based in any US office location and is hybrid with 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.

Responsibilities

• Build and ship components of multi-agent systems and RAG pipelines for PE-backed portfolio company engagements, under the guidance of more senior engineers
• Contribute to prompt engineering, tool design, and deployment for production AI systems
• Write and run evals as part of eval-driven development—define success criteria before you build, not after
• Help translate client requirements into technical tasks, with support from your pod on the ambiguous parts
• Build observability into the systems you ship so quality is measurable, not assumed
• At the Senior level: independently own a workstream (an agentic pipeline, a RAG system, or an eval framework) end-to-end, and present your own architecture decisions to internal and client stakeholders

Success in the first 6 months

• Associate: productive on an active client engagement within 30 days; shipping real code and learning the client's data landscape quickly; contributing meaningfully to at least one production system by month 6
• Senior: shipped at least one end-to-end agentic solution from scoping through production; owns a workstream independently; has built enough credibility with the pod and the client to be trusted with the next hard problem without heavy hand-holding

Requirements

• Solid Python and/or TypeScript/React fundamentals—you write clean code and can reason about what a framework is doing underneath it
• Some hands-on exposure to LLM application development: RAG, tool use, prompt engineering, or agent orchestration (production experience preferred; strong coursework/side-project depth considered for Associate level)
• Genuine use of AI coding tools (Claude Code, Cursor, or similar) in your own workflow—you should be able to talk concretely about where they speed you up
• Comfort with ambiguity and a fast pace—you won't always get a clean spec, and that's the job
• Willingness and ability to learn quickly in a client-facing, consulting-style environment

Preferred qualifications

• Finance/PE domain exposure—FP&A, GL data, ERP systems (NetSuite, SAP)
• Familiarity with LangChain/LangGraph, AutoGen, DSPy, or similar orchestration frameworks
• Public work you can point to: a GitHub repo, a side project, a blog post—anything that shows how you think about building
• Prior internship, co-op, or junior role with client- or user-facing exposure

Pay

The annual salary for this role ranges from $110,000 to $200,000 USD + bonus + benefits, spanning both levels in this posting. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to level, geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity.

Schedule

Hybrid role with flexibility to work remotely 2 days per week. Based in any US office location; candidates should be local to the desired location.

This posting is for a current vacancy and the employer intends to fill this position by December 9, 2026.