Engineer, Software Quality

• Own delivery end to end: from discovery and success metrics to production go-live.
• Shape the solution: turn ambiguous client problems into clear architectures, roadmaps and scoped use cases.
• Build production systems: services, data pipelines and integrations with payment platforms.
• Deploy AI and agents: fraud and risk models, dispute automation, reconciliation agents.
• Accelerate with AI: use AI assistants and automation to speed delivery, picking the best tool for the job.
• Engineer for compliance: PCI DSS, data privacy and auditability by design.
• Champion the customer: be the client’s trusted partner, responsive, accountable and focused on their success.
• Sell and ideate with leadership: co-create AI strategy with senior executives, pitch solutions and grow the account.

TECHNICAL SKILLS

• Software Engineering: Python, Java or Go; APIs and microservices; Kubernetes; AWS/GCP/Azure
• Data Engineering: SQL, Spark/Databricks, Snowflake; streaming pipelines; Workflow Automation
• AI / ML: Statistics, DIPP Analytics; Fraud & Risk Modeling (XGBoost, PyTorch); MLOps;
• Agentic AI: RAG, tool calling, multi-agent orchestration (LangGraph, MCP); evals and guardrails
• Payments: Card networks, ISO 8583/20022, ACH, RTP, SEPA, SWIFT; settlement; PCI DSS, KYC/AML

• 6+ years shipping production software; 3+ in a single industry across functions / horizontals
• Hands-on across backend, data and ML/LLM systems
• Track record of client-facing delivery to production
• Clear communicator from engineers to Leadership Stakeholders
• Builds with AI tools daily; quick to adopt new ones

Preferred

• Built fraud, disputes or reconciliation platforms at a PSP, bank or network
• Shipped LLM agents in a regulated environment
• Prior Forward Deployed Engineer or Data Science role experience
• Experience with payment hubs or core banking (FIS, Fiserv, ACI)