A compliance-first systems mindset you instinctively reach for state machines, idempotency keys, exactly-once semantics, reconciliation jobs and immutable audit logs. You understand that in compliance, false negatives cost millions and false positives cost trust, and you design accordingly. Prior experience in KYC, AML, sanctions, fraud, or payments is a strong plus; experience surviving a regulatory audit is an even stronger plus.
Daily, fluent use of modern AI coding tools Claude Code, Cursor, GitHub Copilot, Codex CLI, or equivalents. You can describe the specific workflows you run, the failure modes you have hit, and the guardrails you have built around AI-generated code. AI fluency is required, not nice-to-have.
Production experience integrating AI/ML model inference into Java services REST/gRPC-based model serving, feature engineering pipelines, latency-sensitive inference optimization, graceful degradation, and drift / rollback playbooks.
Hands-on experience with LLM application patterns at least one of: RAG pipelines (vector store + retrieval + grounding) for policy / KYC / case lookup, agentic workflows (tool use, multi-step reasoning, validation loops) for analyst assistance, or LLM-based classification / extraction shipped to production.
Discipline around AI output you do not ship LLM features without evals, hallucination tests, prompt regression suites, and human-in-the-loop review for high-stakes decisions. You have an opinion on when to reach for a frontier model vs. a fine-tuned small model vs. a deterministic rule, and can defend that trade-off to a regulator.
Exposure to LLM integration or AI agent frameworks is a strong plus e.g. prompt engineering at the system level, RAG pipelines, or orchestrating AI workflows within a regulated environment.
Good understanding of software engineering basics, distributed system principles, including CAP, consistency, idempotency, and exactly-once vs at-least-once semantics.
Clear logic, quick thinking, and good communication skills including the ability to write clearly for non-engineers (compliance officers, auditors, regulators).
