Design and own the architecture of core fintech product services
Define service boundaries, data ownership, and consistency models for high throughput, low latency systems.
Architect and review Java / Spring Boot services with strong focus on performance, resilience, and observability.
Design and implement AI Agent workflows using agentic AI frameworks (e.g., LangGraph) for product use cases such as:
Workflow automation
Operational decision support
Exception or risk triage
Architect multi‑agent orchestration with clear role separation (planner, executor, validator) and deterministic control over execution.
Design agent memory strategies:
Short-term/session memory
Long-term structured memory
Memory scoping, retention, and auditability
Ensure security, compliance, and governance for AI driven flows:
Guardrails and approval steps
Traceability of agent decisions
Safe fallbacks and human-in-the-loop controls
Collaborate closely with product, engineering, and compliance teams to translate requirements into scalable architecture.
Mentor senior engineers and contribute to architecture reviews and technical standards.
Required Qualifications
12–15 years of total experience in backend engineering with Java/Python and modern frameworks. Must have minimum 2 years hands on experience in AI & ML
Strong experience designing distributed, transactional systems in fintech or regulated domains.
Deep understanding of data consistency, idempotency, fault tolerance, and scalability.
Hands‑on experience building stateful AI agents with well‑defined short‑ and long‑term memory.
Solid understanding of security, observability, and production incident handling.
Ability to communicate architectural decisions and trade-offs clearly.
Nice to Have
Experience with event driven architectures (Kafka, async messaging).
Exposure to payments, risk, fraud, reconciliation, or compliance workflows.
Familiarity with AI cost control, evaluation, and governance practices.
