AI Automation Engineer for Finance & Operations

Apptegy

Atlanta (GA)

On-site

USD 115,000 - 135,000

Full time

2 days ago

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Benefits offered by this job

Private medical insurance

Life insurance

15 days Aguinaldo

Vales de Despensa

Fondo de Ahorro

Caja de Ahorro

Flexible paid time off policy

Paid travel to/from Little Rock, AR

Job summary

Apptegy in Atlanta, GA is hiring an AI Automation Engineer who builds durable AI-powered workflows to unlock efficiency across finance and operations, connecting NetSuite, Salesforce, Snowflake and more via APIs. You'll partner with process owners and AI Champions to map workflows and move from prototype to production.

Ideal candidate has 2-4+ years in technical/ops roles, scripting proficiency, and hands-on experience with AI tooling (Claude, N8N, Glean).

Qualifications

2-4+ years in a technical, operations, or automation-focused role such as solutions engineering, business systems, RevOps, or technical program management.
Working proficiency in at least one scripting language, plus experience integrating systems via APIs, webhooks, and data flows.
Hands-on production experience with modern AI tooling such as Claude / Claude Code, Cursor, agent frameworks, MCP, or N8N, and informed opinions about when each is the wrong choice.
Real depth in at least one enterprise business system and its data model.
Strong cross-functional collaboration skills with the ability to translate business needs into clear, actionable technical solutions.
A builder’s mindset that is creative, curious, and eager to experiment with new technologies to drive efficiency.
Excellent communication skills and comfort working with multiple stakeholders in a fast-moving environment.

Responsibilities

Find the work by partnering with process owners to map how work actually happens today, including the exceptions, the workarounds, and the steps that only live with a user.
Size it before you build it by defining the metric and stating the expected result up front, whether that is hours removed, cycle time, error rate, or cost avoided, then measuring the actual result once it ships.
Build and automate smart workflows using AI agents and skills, API integrations, SQL and Python, workflow orchestration, and scripting against the systems where the work lives, taking each one from prototype to production.
Own the connective layer by moving data cleanly between NetSuite, Salesforce, DealHub, Workday, Greenhouse, Snowflake, and the rest of the stack through APIs, webhooks, and pipelines, including the reconciliations that prove both sides agree.
Multiply the builders already in each function by publishing the shared primitives, patterns, and templates they need, so capability compounds instead of queueing behind one person, and by maintaining the automation inventory, including retiring what no longer earns its place.