• Architect and implement customer-facing data and intelligence APIs with clear versioning, SLAs, and backward compatibility. • Define and enforce API contracts for: Low latency, high throughput endpoints; Agentic workflows (tools, actions, state transitions, handoffs); Context retrieval and enrichment. • Design APIs as durable platform interfaces, not thin wrappers over storage systems. • Establish standards for schema governance, payload design, and service boundaries. • Architect service layers that support agentic workflows, including orchestration interfaces, guardrails, and runtime observability. • Build API surfaces that expose model outputs safely and consistently. • Collaborate with MLEs and Data Scientists to move models from experimentation into robust inference services. • Ensure proper lifecycle management, monitoring, and rollback mechanisms for ML-powered endpoints. • Design and implement service layers that sit on top of the gold-layer system of record. • Build and evolve context hubs derived from authoritative systems of record, enabling consistent entity, identity, or risk context for downstream services. • Ensure APIs are aligned with medallion architecture principles and platform data contracts. • Prevent fragmentation by maintaining strong coupling to canonical schemas and governed data models. • Design high-throughput, low-latency services supporting batch and streaming workloads. • Implement scalable infrastructure patterns on AWS. • Ensure strong observability, error handling, performance tuning, and cost awareness. • Drive infrastructure-as-code practices and production readiness standards. • Serve as a senior architectural voice in design reviews. • Raise the bar on code quality, system design, and operational rigor. • Mentor engineers on API design, distributed systems, and ML integration patterns. • Influence platform direction through technical depth rather than organizational authority.