Senior AI Engineer
Summary
Design and build an AI-driven payments automation layer using LLM orchestration and multi-agent systems, while ensuring compliance and scalability in a regulated financial environment.
Own the long-term architecture and evolution toward an AI
Key Responsibilities
Assess and map end-to-endoperations, 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
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:
- Cost reduction
- 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
Technical Expertise
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
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