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Decagon

AI Acceleration Engineer

San Francisco$180k–$220kfulltimemidAdded today

About this role

Decagon seeks an AI Acceleration Engineer to build internal systems and automations that embed AI into business operations across Finance, Accounting, and other departments. You'll own full-lifecycle projects—from design through deployment—automating manual processes like billing and collections while enabling teams to leverage AI agents and tools for their own workflows.

What you'll do

  • Own end-to-end projects including requirements gathering, solution design, development, testing, deployment, and maintenance
  • Build web applications and integrations for internal teams, including contract management, revenue platforms, and new tools from scratch
  • Partner with stakeholders across Finance, Accounting, Legal, People, and Recruiting to identify automation opportunities and recommend custom builds, AI vendors, or hybrid solutions
  • Develop MCP servers, skills, and agent-facing tooling that enable non-technical users to automate workflows
  • Execute major workstreams such as billing, revenue recognition, usage data ingestion, and reconciliation across internal systems, ERPs, and Salesforce
  • Measure and report impact to leadership: time saved, costs reduced, errors eliminated

What they're looking for

  • Full-stack web application development
  • Internal tools and business systems engineering
  • Revenue operations and finance systems experience
  • AI-native coding tools (Claude Code, Cursor, Codex)
  • System design and data architecture fundamentals
  • API integrations and ERP/Salesforce integration
  • Agentic AI and LLM application development
  • Stakeholder management and requirements gathering
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Decagon

Decagon builds enterprise-grade conversational AI platforms that enable organizations to deploy AI agents for business impact. The company is hiring Strategic Solutions Engineers, Customer Engineers, Platform Engineers, and systems-focused engineers to deliver AI implementations, build internal infrastructure, and establish security practices across their growing platform.

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Likely interview questions

  • Walk us through a full-lifecycle project you owned from requirements to production—what were the biggest challenges in maintaining it long-term?
  • Tell us about a time you had to decide between building a custom solution versus adopting an existing tool or vendor. What was your decision-making process?
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