AI Deployment Strategist
Build and deploy AI agent workflows for finance teams, partnering with customers and engineers to identify use cases, optimize outputs, and drive adoption. The role requires 1–3 years supporting finance teams, strong accounting knowledge, SQL proficiency, and comfort with AI automation.
About the job
Responsibilities
- Design, configure, and tune AI agent workflows using customers’ data, systems, and reporting conventions.
- Maintain prompt libraries, tune model configurations, and improve output quality for finance use cases.
- Map finance-team workflows and prioritize high-value, repeatable use cases for automation.
- Scope, build, and launch customer deployments with the forward-deployed engineering team.
- Create dashboards and analytics covering customer behavior, product usage, and revenue expansion opportunities.
- Identify customer patterns to improve positioning, messaging, onboarding playbooks, and expansion strategies.
- Optimize onboarding, training, and lifecycle experiences to accelerate first value and long-term adoption.
- Develop customer segmentation, health scoring, expansion signals, and proactive account-insight systems.
- Design scalable agent capabilities and prompts across ERPs, banks, CRMs, HRIS tools, and custom databases.
Requirements
- 1–3 years of experience in finance, investment banking, consulting, FP&A, finance operations, or data and systems roles supporting finance teams.
- Strong understanding of financial statements, accounting principles, finance-team operations, and recurring finance workflows.
- Experience with vibe-coding and enthusiasm for using AI to automate systems.
- Proficiency in SQL, including analysis queries, evaluation-set development and testing, debugging, and customer-data work.
- Familiarity with BI tools and data warehouses.
- Ability to work independently and take ownership in a fast-paced, ambiguous startup environment.
Nice-to-haves
- Experience with finance systems such as QuickBooks Online, Ramp, NetSuite, Intacct, Oracle, SAP, or Salesforce.
- Experience with LLMs, prompt engineering, or tuning AI outputs for analytical or operational workflows.
- Familiarity with Looker, Tableau, Power BI, Snowflake, BigQuery, or PostgreSQL.
Compensation and Benefits
- Top-of-market salary and equity.
- High ownership, direct founder mentorship, and opportunities to develop skills across engineering, AI, and go-to-market functions.
Skills
SQL, Prompt Engineering, LLMs, AI Agents, Analytics, Looker, Tableau, Power BI, Snowflake, BigQuery, Postgres, NetSuite, SAP, Salesforce, Financial Modeling
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