AI Engineer

Own the long-term architecture and evolution toward an AI

Assess and map end-to-end operations
, including:

• Reconciliations
• Reporting & controls
• Audit

Identify:

• Operational bottlenecks
• Capability gaps

Define a Payments automation roadmap based on:

• Operational impact
• Regulatory risk
• Scalability

Design the AI System
, including:

• Integration with financial systems
• Control and reporting frameworks

Design and implement an agentic Payments layer that:

• Operates alongside the current stack
• Automates workflows today
• Enables gradual migration to a future-state architecture
• Evaluate and simplify the existing Payments technology stack
• Represent Payments in the AI Center of Excellence
  , ensuring alignment across teams

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

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

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

• LLM orchestration
• Multi-agent systems
• AI failure modes in high-stakes environments

• Spring AI/Python-based orchestration
• Workflow engines (n8n or equivalent)
• AI APIs (Anthropic/Claude or similar)

Strong architectural thinking for scalable, future-ready platforms

Operates effectively in fast-paced, ambiguous environments

Strong ownership mindset with a bias for execution

Ability to bridge business and engineering domains