Senior AI Engineers - Agentic Development & AI-Augmented Engineering

Senior AI Engineers - Agentic Development & AI-Augmented EngineeringResponsibilitiesDesign and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changesArchitect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to useDefine human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changesBuild evaluation harnesses and observability practices to measure agent output quality and catch regressionsDesign and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principlesDrive test-driven development practices across teams, including contract testing between servicesOwn technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python toolingDesign REST APIs and headless component architectures that support both human developers and AI agentsEstablish CI/CD practices that safely incorporate agent-authored pull requestsSet and enforce security practices for agentic workflows, including prompt injection risk and tool-permission boundariesMentor senior and staff engineers on effective agent-assisted developmentWrite RFCs and design docs that translate ambiguous problems into actionable technical plans, documents that both humans and agents can act onRequired Skills & ExperienceAgentic DevelopmentHands-on experience with Claude Code or comparable agentic coding tools in production settingsStrong understanding of MCP (Model Context Protocol) building and consuming MCP serversContext engineering: managing context windows, prompt caching, and information architecture for long-running agent sessionsAwareness of prompt injection and agent-specific security risksArchitecture & BackendDeep experience with Java microservicesStrong REST API design skillsC4 model architecture documentation and system designDomain-Driven Design principlesNode.js and Python for tooling, services, and automationMongoDB schema design, performance, and scalingFrontendReactJS, headless component architecture, and microfrontend design patternsTesting & QualityTest-driven development (TDD) as a core practice, not an afterthoughtPlaywright for end-to-end testingContract testing (e.g.