AI Automation and Integration Engineer

Summary

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.

Our client operates a large verified healthcare professional community spanning approximately 150 countries and provides real‑time research and data products for pharmaceutical, biotech, and medical device clients.

Role Overview

The AI Automation and Integration Engineer, Finance and Revenue Operations will embed with Finance and Revenue Operations teams to identify, prioritize, design, and build high‑impact AI‑first workflows across reporting, internal systems, and administrative processes.

This is a discovery‑led engineering role responsible for determining which automation opportunities should be addressed first and then owning their design and implementation. The goal is to redesign workflows so AI agents can perform recurring work while people provide verification and oversight, with the controls, approvals, validation, and auditability required for finance operations.

Location

Fully Remote | European time zones with overlap with London working hours

Key Responsibilities

Process Discovery & Automation Strategy

• Embed with Finance and Revenue Operations to map processes, systems, reporting requirements, approval flows, and operational pain points.
• Establish measurable baselines for existing processes before implementing automation.
• Lead discovery sessions and prioritize opportunities based on impact, complexity, data availability, and risk.
• Separate quick‐win automation opportunities from longer‐term systems initiatives.
• Build a repeatable framework for identifying, evaluating, and scaling future AI automation opportunities.

AI Workflow & Agent Development

• Redesign and build AI‑powered workflows, agents, integrations, and internal tools.
• Develop workflows that enable AI agents to perform recurring work while maintaining appropriate human verification and oversight.
• Build solutions across financial reporting, internal systems, administrative processes, and other Finance and Revenue Operations workflows.
• Explore natural‑language interfaces that provide trustworthy access to business and financial data without requiring manual data requests.
• Determine when automation platforms or purpose‑built AI agents are appropriate for specific workflows.

Finance Systems & Integrations

• Integrate finance systems, planning tools, data platforms, and business applications.
• Identify practical integration approaches for cloud ERP environments, including alternatives where direct extensibility is limited.
• Build and maintain integrations using APIs, webhooks, and structured data flows.
• Support AI‑assisted workflows across accounting, planning, invoice capture, payment processing, and data platforms.
• Support automation across accounts receivable, credit control, and cash‑collection communication.

Controls, Governance & Reliability

• Design human‑in‑the‑loop approvals into finance workflows.
• Implement role‑based access, data validation, exception handling, and audit trails.
• Ensure workflows have clear operational ownership and appropriate controls.
• Support secure handling of sensitive business data within AI‑enabled workflows.

Measurement & Documentation

• Measure time saved, manual work removed, and adoption against established process baselines.
• Document architecture, workflow logic, controls, and operating procedures.
• Evaluate automation impact using defined success metrics.
• Develop prioritized roadmaps for future automation initiatives.

Cross‑Functional Collaboration

• Work closely with Finance, Revenue Operations, Data, and Engineering teams.
• Translate ambiguous processes and requirements from non‑technical stakeholders into practical technical solutions.
• Build stakeholder buy‑in for AI‑powered workflows and automation initiatives.
• Independently take projects from directional guidance and discovery through implementation and adoption.

Qualifications

Experience

• 5+ years of software engineering experience , including 2+ years building and deploying AI‑powered workflows, agents, or integrations in production .
• Experience completing an agent‑first redesign of a real business workflow, including establishing a baseline, redesigning the workflow, defining human involvement, and measuring results.
• Strong experience with APIs, webhooks, data flows, and systems integration.
• Experience developing in Python and at least one typed programming language.
• Experience with SQL, structured data, reporting systems, and data warehouses.
• Experience with business systems such as ERPs, finance platforms, databases, reporting tools, or internal operational software.
• Experience building workflows that incorporate data validation, approvals, exception handling, auditability, and clear operational ownership.
• Proven ability to translate ambiguous processes from non‑technical stakeholders into practical technical solutions.
• BS in Computer Science or a related field, or equivalent practical experience.

Skills

• Strong integration engineering skills across APIs, webhooks, data flows, and business systems.
• Strong Python development skills and experience with at least one typed language.
• Strong SQL and structured data skills.
• Ability to design and deploy production AI workflows and agents.
• Ability to establish process baselines and measure the impact of automation initiatives.
• Strong understanding of human‑in‑the‑loop workflows, role‑based access, validation, exception handling, and auditability.
• Ability to independently prioritize and execute automation initiatives based on impact, complexity, data availability, and risk.
• Ability to document technical architecture, workflow logic, controls, and operating procedures.

Preferred Experience

• Experience with cloud ERP platforms such as SAP Business ByDesign.
• Experience with financial reporting, FP&A, accounting operations, invoice capture, or payment processing workflows.
• Experience with platforms such as Cube, Amazon Redshift, Databricks, Odoo, or Opayo.
• Experience building natural‑language data interfaces or AI‑assisted business analysis solutions.
• Experience with Zapier or similar automation platforms.
• Experience in enterprise SaaS, healthcare, finance, or other data‑sensitive environments.
• Experience with AI governance, access controls, and secure handling of business data.

Technical Environment

• SAP Business ByDesign
• Cube
• Odoo
• Opayo
• Amazon Redshift
• Databricks
• AWS
• C#/.NET
• TypeScript
• Amazon Bedrock
• AgentCore
• Claude models

What Success Looks Like

First 30 Days

• Build relationships with Finance, Revenue Operations, Data, and Engineering.
• Map the finance technology landscape, including ownership, data flows, recurring reports, manual processes, and controls.
• Rank automation opportunities and select the first pilot.
• Establish the pilot’s success metric, baseline, approvals, and rollout plan.

First 60 Days

• Have the pilot running with a small group of users in shadow mode.
• Implement required integrations, data‑quality checks, access controls, and approval steps.

First 90 Days

• Launch at least one workflow into production for Finance or Revenue Operations.
• Demonstrate measurable impact against the established baseline.
• Establish a repeatable framework for identifying and scaling additional automation opportunities.
• Develop a prioritized roadmap for the next wave of AI automation initiatives.