Who You Are You have experience building Retrieval‑Augmented Generation (RAG) systems or knowledge‑base chatbots. You're Hands‑on with vector databases such as Pinecone, Chroma, or pgvector on Postgres/Aurora. Have AWS certification (Developer, Solutions Architect, or Machine Learning Specialty). Experience with observability tooling (Datadog, New Relic) and cost‑optimization strategies for AI workloads. Background in microservices, domain‑driven design, or event‑sourcing patterns. What You’ll Actually Be Doing Design, build, and continuously improve our LLM-based Agentic platform. Own end-to-end architecture decisions from model orchestration and prompt design to retrieval pipelines, tool-calling patterns, and evaluation frameworks. Architect and build high-performance services in Python and/or Node.js. Design systems for extreme speed, reliability, and real-time data processing under high traffic conditions. Design and maintain MCP servers that give AI agents structured, secure access to internal banking systems, external APIs, databases, and developer tools making Agentic platform composable and extensible by design. Build intuitive React interfaces that expose AI capabilities like chat interfaces, agentic dashboards, real-time streaming UIs, and internal tooling. Own state management patterns and component architecture at scale. Partner with product managers, business stakeholders, compliance, and engineering teams to translate vision into scalable technical requirements and roadmaps. Design and ensure the platform meets enterprise-grade security and financial regulatory standards. Actively upskill fellow engineers on full-stack best practices, LLM integration patterns, and production of AI systems. Help define coding standards and contribute to a culture of engineering excellence. Evaluate emerging models, frameworks, and tooling. Prototype and integrate the most impactful advances into our platform and internal developer productivity tooling. Requirements Wh
