While many job lists use the term "AI agent" loosely, this brief strictly focuses on roles genuinely tied to agentic systems work. By examining official application pages on May 6, 2026, we've identified and included only openings that are live, clearly related to building, deploying, operating, or evaluating AI agents, and explicitly linked to agentic systems.
Our filtering criteria included:
- The application page was live on an official ATS page on May 6, 2026.
- The role was remote or clearly online-compatible.
- The posting explicitly described building, deploying, operating, or evaluating AI agents.
- A direct application link is included for each role.
Why this list is structured as a technical brief:
To provide a clearer understanding of where companies are concentrating their engineering efforts in the AI-agent space, this list organizes roles by the specific layer of the AI-agent stack they represent, rather than just listing links.
1. Deployment layer: Cresta
Cresta is seeking an engineer for a role focused on production deployments rather than lab experimentation. The position involves developing, configuring, deploying, and optimizing AI agents using Cresta's platform, while also integrating these agents with APIs, databases, CRMs, and other enterprise systems.
This role is genuinely agent-focused due to its mix of responsibilities: prompt/config tuning, AI-agent deployment, customer requirements gathering, awareness of Retrieval-Augmented Generation (RAG) and Function Calling, and hands-on work transforming business workflows into real agent behavior. It is not a generic solutions engineer role with superficial AI components; the job description consistently centers on AI agent systems.
Concrete signals from the posting:
- Deployment and optimization of AI agents are explicitly called out as core responsibilities.
- It references integration with external systems and enterprise workflows.
- Preference is given to hands-on experience with agent frameworks, function calling, and RAG.
- The compensation band is published at $185,000-$235,000 base plus bonus and equity, indicating a serious, production-grade role.
Why it's on this list: This exemplifies the "agent deployment engineer" archetype—the professional responsible for making agents work effectively in complex, high-stakes customer environments.
2. Character and multimodal layer: Saga
Saga's posting is unique as it's not about generic copilots or enterprise automation. Instead, it focuses on building and operating character AI agents at scale for creators, studios, and publishers. The role description indicates the engineer will work across the full lifecycle of agent systems, including fine-tuning models, orchestrating Large Language Model (LLM) and Small Language Model (SLM) swarms, and deploying agents across social platforms.
