AI Payments Engineering Team Lead

The Focus Group; Sandton; On-site; ZAR 1,200,000 - 1,800,000; Full time

Job summary

The Focus Group in Sandton is 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. You will deploy agentic workflows for reconciliations, audit, and analytics using Claude/Anthropic APIs, Java Spring AI, and n8n.

Qualifications

• Hands-on experience deploying production-grade AI/agentic systems.
• Strong understanding of LLM orchestration and multi-agent architectures.
• Proficiency in Spring AI and Python-based orchestration.
• Experience with AI tooling and API integrations for payments.

Responsibilities

• Design and deploy production-grade AI automation workflows.
• Build agentic workflows for reconciliations, audit, and analytics.
• Integrate internal and external systems via APIs and data pipelines.
• Ensure workflows are auditable, compliant, and risk-aware.
• Collaborate with Payments, Infra, Compliance, and AI teams.

Skills

AI workflow design

LLM orchestration

Multi-agent systems

Python orchestration

Spring AI

n8n

Tools

Claude API

Anthropic APIs

n8n

Spring AI

Python

Job description

Description:

We are building a next-generation AI Payments Engineering Teamto design and deliver an AI-native Payments Operating System.

This team will combine AI engineering, payments domain expertise, and production automationto 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 automationetc.

The mission is to deliver efficiency with control integrity---not just automation speed. This team should have ability to build, test, deploy and maintain (solution and platform) the entire solution.

Core Focus

Design and deployproduction-grade AI automation workflowsthat drive immediate operational impact.

Key Responsibilities

• Build and deployagentic workflowsfor:
• 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
• Integrateinternal and external systemsvia:
• APIs
• Data pipelines
• Reporting systems
• Reduce manual effort by identifyingautomation opportunities across Payments operations
• Maintainhuman oversight and approval controlswhere required
• Ensure all workflows areproduction-ready, auditable, and compliant

AI Governance & Risk Management

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

Platform & Capability Building

• Developreusable frameworks, templates, and workflows
• Createdocumentation and standardsto scale adoption
• Builddashboards and metricsto measure:
• Efficiency gains
• Cost reduction
• Risk outcomes
• ROI
• Train Payments teams onAI-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 intotechnical solutions and roadmaps
• Communicate effectively withtechnical and non-technical stakeholders

What the Team Brings

Technical Expertise

• Hands-on experience deployingproduction-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 forscalable, future-ready platforms

Ways of Working

• Operates effectively infast-paced, ambiguous environments
• Strong ownership mindset with abias for execution

Ability to bridge business and engineering domains