AI Engineers - Agentic Development & AI-Augmented Engineering

Senior AI Engineers - Agentic Development & AI-Augmented Engineering- Hoboken, NJ Onsite

Responsibilities

• Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes
• Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use
• Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes
• Build evaluation harnesses and observability practices to measure agent output quality and catch regressions
• Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles
• Drive test-driven development practices across teams, including contract testing between services
• Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling
• Design REST APIs and headless component architectures that support both human developers and AI agents
• Establish CI/CD practices that safely incorporate agent-authored pull requests
• Set and enforce security practices for agentic workflows, including prompt injection risk and tool-permission boundaries
• Mentor senior and staff engineers on effective agent-assisted development
• Write RFCs and design docs that translate ambiguous problems into actionable technical plans, documents that both humans and agents can act on

Required Skills & Experience



Agentic Development

• Hands-on experience with Claude Code or comparable agentic coding tools in production settings
• Strong understanding of MCP (Model Context Protocol) building and consuming MCP servers
• Context engineering: managing context windows, prompt caching, and information architecture for long-running agent sessions
• Awareness of prompt injection and agent-specific security risks

Architecture & Backend

• Deep experience with Java microservices
• Strong REST API design skills
• C4 model architecture documentation and system design
• Domain-Driven Design principles
• Node.js and Python for tooling, services, and automation
• MongoDB schema design, performance, and scaling.

Frontend

• ReactJS, headless component architecture, and microfrontend design patterns

Testing & Quality

• Test-driven development (TDD) as a core practice, not an afterthought
• Playwright for end-to-end testing
• Contract testing (e.g., Pact) across microservice boundaries