AI Automation Engineer

cpconsulting; Johannesburg; On-site; ZAR 1,200,000 - 1,800,000; Full time

Job summary

cpconsulting is building a next-generation AI Payments Engineering Team to design and deliver an AI-native Payments Operating System that automates high-risk financial operations with auditable controls.

The role focuses on deploying agentic workflows, integrating APIs and data pipelines, and driving governance, risk management, and platform scaling to achieve measurable efficiency and reliability.

Qualifications

• Hands-on experience deploying production-grade AI/agentic systems.
• Strong knowledge of LLM orchestration and multi-agent systems.
• Proficiency with Spring AI and Python-based orchestration.

Responsibilities

• Build and deploy agentic workflows for reconciliations, audit & analytics tasks.
• Integrate internal and external systems via APIs and data pipelines.
• Ensure workflows are auditable, compliant, and production-ready.

Skills

AI automation

Payments operations

Workflow orchestration

Stakeholder communication

Tools

Claude API

Spring AI

Python

n8n

MCP

Job description

We are building a next-generation AI Payments Engineering Team to design and deliver an AI-native Payments Operating System. This team will combine AI engineering, payments domain expertise, and production automation to transform high-effort, high-risk financial operations into scalable, intelligent, and auditable systems. The team will focus on automating critical Payments processes such as Least cost routing, reconciliations, audit, Incident automation, etc. The mission is to deliver efficiency with control integrity—not just automation speed. This team should have the ability to build, test, deploy, and maintain (solution and platform) the entire solution.

Requirements Core Focus

Design and deploy production-grade AI automation workflows that drive immediate operational impact.

Key Responsibilities

• Build and deploy agentic workflows for:
  • Reconciliations
  • Audit & reporting preparation
  • Financial analytics
• Use modern AI tooling:
  • Claude / Anthropic APIs
  • Java (Spring AI)/Python orchestration
  • n8n (or equivalent workflow engines)
  • MCP or similar multi-agent coordination layers
• Integrate internal and external systems via:
  • APIs
  • Data pipelines
  • Reporting systems
• Reduce manual effort by identifying automation opportunities across Payments operations
• Maintain human oversight and approval controls where required
• Ensure all workflows are production-ready, auditable, and compliant

AI Governance & Risk Management

• Classify all automation by risk tier before development
• Ensure each solution includes:
  • Named Process Owner
  • Documented data flows
  • Access controls
  • Full audit logging
• Design automation that preserves control integrity in regulated environments

Platform & Capability Building

• Develop reusable frameworks, templates, and workflows
• Create documentation and standards to scale adoption
• Build dashboards and metrics to measure:
  • Efficiency gains
  • Cost reduction
  • Risk outcomes
  • ROI
• Train Payments teams on AI-enabled workflows and tools

Collaboration & Stakeholder Engagement

• Work closely with:
  • Payments Backend teams
  • Infrastructure & platform teams
  • Compliance & audit teams
  • AI Center of Excellence
• Translate business and finance requirements into technical solutions and roadmaps
• Communicate effectively with technical and non-technical stakeholders

What the Team Brings

Technical Expertise

• Hands-on experience deploying production-grade AI/agentic systems
• Strong understanding of:
  • LLM orchestration
  • Multi-agent systems
  • AI failure modes in high-stakes environments
• Proficiency in:
  • Spring AI/Python-based orchestration
  • Workflow engines (n8n or equivalent)
  • AI APIs (Anthropic/Claude or similar)

Systems & Architecture Thinking

• Ability to deliver across the lifecycle: Discovery → Design → Build → Deploy → Optimize
• Strong architectural thinking for scalable, future-ready platforms

Ways of Working

• Operates effectively in fast-paced, ambiguous environments
• Strong ownership mindset with a bias for execution
• Ability to bridge business and engineering domains