AI Engineer - Agentic Systems

Summary We are seeking a highly hands-on AI Engineer with a proven track record of shipping agentic AI systems into production for enterprise environments.

In this role, you will design, build, and deploy production-grade AI agents capable of multi-agent orchestration, complex tool execution, and dynamic context management. You will implement robust safety guardrails and integrate frontier models using leading agent frameworks and cloud infrastructure.

This position is remote within the US (East Coast time zone slightly preferred) with minimal travel required. Tasks and Deliverables Design and deploy autonomous and multi-agent orchestration workflows capable of executing complex, multi-step enterprise processes.

Implement structured tool-use frameworks and integrate external APIs and services using protocols such as Model Context Protocol (MCP). Engineer advanced prompt strategies, dynamic context management, and memory layers to optimize model performance and reasoning accuracy.

Implement production-grade guardrails, schema enforcement, latency optimization, and defensive exception handling across all agentic workflows. Deploy, scale, and maintain agentic microservices on cloud infrastructure using modern containerized and serverless platforms.

Required Experience Production Agent Experience: Demonstrated, hands-on software engineering experience building, testing, and shipping autonomous agent systems and tool-calling workflows into production environments.

Framework & Model SDK Expertise: Strong proficiency in at least one major model ecosystem: Anthropic (Claude Agent SDK, Model Context Protocol), OpenAI (OpenAI Agents SDK, Responses API, File Search), or GCP Vertex AI (Gemini, Google ADK / Vertex AI Agent Engine).

Cloud Infrastructure (GCP): Experience building and deploying distributed applications on Google Cloud Platform, using services such as GKE, Cloud Run, Pub/Sub, and BigQuery. Core Software Engineering: Strong foundation in software design patterns, AP