AI Engineer - Agentic Systems

We’re looking for a hands-on AI Engineer who has already shipped agentic AI systems into production for enterprise environments — not prototypes, not demos, but agents that real users and real business processes depend on. You’ll design, build, and deploy production-grade AI agents that orchestrate across multiple agents, execute complex tool calls, and manage context dynamically. You’ll integrate frontier models through leading agent frameworks, put robust safety guardrails in place, and run it all on cloud infrastructure built to scale.

This is a remote role for engineers based in the United States, with a slight preference for the East Coast time zone.

What You’ll Do

• Build multi-agent workflows. Design and deploy autonomous and multi-agent orchestration workflows that carry out complex, multi-step enterprise processes end to end.
• Wire agents into the real world. Implement structured tool-use frameworks and integrate external APIs and services using protocols such as the Model Context Protocol (MCP).
• Engineer context and memory. Develop advanced prompting strategies, dynamic context management, and memory layers that improve model performance and reasoning accuracy.
• Make agents production-safe. Implement production-grade guardrails, schema enforcement, latency optimization, and defensive exception handling across every agentic workflow.
• Run it at scale. Deploy, scale, and maintain agentic microservices on cloud infrastructure using modern containerized and serverless platforms.

What You Bring

• Production agent experience. A demonstrated, hands-on track record of building, testing, and shipping autonomous agent systems and tool-calling workflows into production.
• Deep fluency in at least one major model ecosystem: Anthropic — Claude Agent SDK, Model Context Protocol
• OpenAI — OpenAI Agents SDK, Responses API, File Search
• Google Cloud — Vertex AI (Gemini), Google ADK / Vertex AI Agent Engine
• Google Cloud Platform experience. You’ve built and deployed distributed applications on GCP using services such as GKE, Cloud Run, Pub/Sub, and BigQuery.
• Strong software engineering fundamentals. Solid grounding in design patterns, API integrations, structured outputs (Pydantic / JSON Schema), and microservices architecture.
• US-based. You live and work in the United States (East Coast time zone slightly preferred).

Nice to Have

• Hands-on experience across more than one of the model ecosystems above
• Experience authoring MCP servers, not just consuming them
• A track record of building evaluation, testing, and observability for agent behavior in production
• Experience working in the East Coast time zone with enterprise stakeholders