AI MLOps Lead - Payments Engineering
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Role Summary
We are looking for a techno-functional leader with deep experience in Payments domain and AI/ML solutions to design and implement intelligent, AI-enabled payment solutions. The role requires someone who can engage with business stakeholders, design AI-driven architectures, and also contribute hands-on to development and deployment, particularly in AI MLOps environments. This is not a pure data scientist role or a pure BA role but a design + build + deploy role within Payments transformation programs.
Key Responsibilities
1. Payments Domain & Functional Leadership
- Work with stakeholders across Payments (Wire, ACH, SWIFT, ISO 20022, Cards, Cross-border, Liquidity)
- Identify AI-led automation and optimization opportunities in payments lifecycle
- Translate regulatory, operational, and reconciliation challenges into AI solution use cases
- Define business requirements and solution blueprints
2. AI Solution Design
- Design AI/ML-driven solutions for:
- Fraud detection & anomaly detection
- Reconciliation automation
3. Hands-on Development
- Develop ML models / AI workflows using Python and relevant frameworks
- Build APIs and integration layers for embedding AI into payments systems
- Work with data pipelines (real-time + batch)
- Implement data preprocessing, feature engineering, and model evaluation
4. AI MLOps & Deployment
- Set up and manage ML lifecycle using MLOps frameworks
- Implement:
- Model versioning
- CI/CD pipelines
- Monitoring & drift detection
- Governance and audit controls
- Ensure production-grade deployment with compliance considerations
5. Stakeholder & Delivery Management
- Interface with product teams, risk teams, operations, and engineering
- Lead POCs and scale into production
- Support proposal creation and AI solution articulation for clients
Domain
- 10+ years of experience in Banking/FinTech
- Strong Payments domain exposure (SWIFT, ISO 20022, Cards, Wire, ACH, Cross-border, Treasury flows)
- Understanding of regulatory and compliance implications in payments
- Experience working in payments transformation programs
Technical
- Strong Python skills
- Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.)
- Experience with LLMs / GenAI frameworks (LangChain, RAG, prompt engineering, etc.)
- Experience in cloud (AWS / Azure / GCP)
- Experience in MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, etc.)
- API development experience
Techno-Functional Capabilities
- Ability to translate business requirements into technical AI designs
- Strong solution architecture capability
- Experience designing and deploying AI solutions end-to-end
Good to Have
- • Fraud / AML AI implementation experience
- • Real-time payments exposure
- • Knowledge of DevOps practices