Five Open AI-Agent Roles That Show Where the Market Is Hiring in May 2026

Five Open AI-Agent Roles That Show Where the Market Is Hiring in May 2026

Most "AI agent jobs" lists are just keyword dumps. I wanted a tighter brief: five live remote postings that together show the actual hiring surface of the agent economy right now.

I checked company-hosted application pages on May 6, 2026 and kept only roles that met all of these conditions:

• the application page was live
• the role was remote or explicitly online-friendly
• the description clearly involved AI agents, agentic systems, autonomous workflows, prompt/eval work for agents, or the commercialization of agent products
• the link went to a direct employer-hosted application page, not a scraped repost

I also avoided talent-pipeline placeholders and stale pages that no longer resolved cleanly.

Snapshot Table

1. Binance — Pioneer Talent Program: AI Application Engineer

Company: Binance

Location: Asia, remote

Direct application: https://jobs.lever.co/binance/2ef11b02-daff-4f10-819e-cb005ff1befd/apply

What the posting is actually about

This is not framed as research-only AI work. Binance is hiring for a practical engineering role focused on shipping agent systems into real operating environments. The application page describes work across:

• agent workflows and LLM-powered systems for business use cases
• tool integration with APIs, internal services, databases, and knowledge sources
• quality, latency, reliability, safety, and cost improvement
• prompt structure, orchestration logic, memory or retrieval patterns, and human handoff design

Why this is a strong AI-agent lead

This is one of the clearest examples of a company asking for the full production-agent toolkit rather than just "prompting experience." The job explicitly connects agents to tools, knowledge stores, operational systems, evaluation loops, and safe rollout practices.

Why it made my top five

It shows that even a junior-to-early-career pipeline program now expects applicants to understand the building blocks of production agent systems: orchestration, retrieval, tool use, guardrails, and iterative improvement. That is a useful signal for anyone tracking where AI-agent hiring is normalizing.

2. PointClickCare — Principal AI Engineer (Autonomous Agent) (US)

Company: PointClickCare

Location: Remote, USA

Direct application: https://jobs.lever.co/pointclickcare/1f8400f8-a731-42f0-b617-574cfcbbd92f/apply

What the posting is actually about

This role sits inside a centralized GenAI team at a healthcare technology company with a large provider footprint. The page describes responsibilities that go beyond building a chatbot:

• designing agent-based solutions aligned with product goals
• building new agent data types and pipelines
• enabling reasoning, function calling, and action coordination
• optimizing autonomous agents with LLMs and planning approaches
• integrating agents with APIs, internal systems, and data sources
• implementing security controls such as authentication, RBAC, audit logging, and compliance monitoring

The posting also lists a concrete compensation band: $179,000-$199,000 base in the US market.

Why this is a strong AI-agent lead

This role is valuable because it treats autonomous agents as a systems-engineering problem, not just a model prompt problem. Healthcare is a domain where security, permissions, and auditability matter. When a hiring post asks for agent reasoning plus access control and compliance monitoring in the same breath, it is a serious signal.

Why it made my top five

It represents the high-accountability end of the market. If Binance shows fast-moving operational agent work, PointClickCare shows what agent hiring looks like in a regulated environment: secure tool use, traceable actions, and production-grade integration requirements.

3. Veeam Software — AI Agents CI/CD DevOps Engineer III

Company: Veeam Software

Location: Remote, United States

Direct application: https://job-boards.eu.greenhouse.io/veeamsoftware/jobs/4834468101

What the posting is actually about

This is a delivery-and-platform role for AI agents rather than a model-building role. The application page focuses on:

• build and deployment pipelines for AI agents and Azure containerized applications
• CI/CD automation across build, test, and release
• GitHub Actions, secure auth, secrets management, and self-hosted runners
• Kubernetes delivery using Helm and AKS
• integrations with artifact repositories, security tools, and adjacent systems

The role also lists familiarity with LLMOps practices, AI-agent architectures, and GitOps-style workflows as bonus knowledge.

Why this is a strong AI-agent lead

A lot of weak job lists over-focus on titles with "AI" in them and miss the supporting infrastructure. This role matters because AI agents only become useful when they can be delivered, updated, observed, and rolled back safely. The hiring brief makes that explicit.

Why it made my top five

It rounds out the stack. A merchant evaluating agent-related opportunities should see that the market is not only hiring people to design agent behaviors; it is also hiring people to industrialize agent deployment.

4. Netomi — Prompt Engineer

Company: Netomi

Location: Toronto, Canada / Remote

Direct application: https://jobs.lever.co/netomi/7fbf062a-4853-4336-a639-f2a607640d38/apply

What the posting is actually about

Netomi positions itself as an agentic AI platform for enterprise customer experience. The Prompt Engineer role is unusually concrete about the work:

• crafting and refining client-specific prompts
• defining tool descriptions for agentic frameworks
• improving prompt performance through automated testing
• evaluating models and benchmarking prompt strategies
• documenting prompt development and optimization decisions
• working with customer success and data science to tailor behavior to business rules

Why this is a strong AI-agent lead

This role is important because it captures the quality-control layer of agent systems. In production customer support or service automation, agents fail less from raw model ignorance than from badly specified tools, weak evaluation, or poor adaptation to customer rules. Netomi is hiring exactly around that layer.

Why it made my top five

It prevents the final list from becoming engineering-only. Prompt/eval work remains a real specialization inside agent companies, especially where customer-specific workflows, compliance expectations, and measurable resolution quality all matter.

5. Cresta — Enablement Manager, AI Agent

Company: Cresta

Location: United States (Remote)

Direct application: https://job-boards.greenhouse.io/cresta/jobs/5118062008

What the posting is actually about

Cresta is hiring someone to help its go-to-market teams consistently position, sell, and deploy its AI Agent product. The posting is detailed about the commercial mechanics:

• educating sellers on AI Agent capabilities, architecture, deployment models, and differentiation
• translating technical behavior into clear value for executive, operational, and technical buyers
• helping teams identify high-impact use cases and tie them to customer KPIs
• building talk tracks, objection handling, and persona-specific messaging
• tracking metrics like ramp time, attach rate, win rate, sales cycle length, and adoption indicators

Why this is a strong AI-agent lead

This is the most important non-builder role in the set. It shows the market has moved beyond "can we build an agent?" into "can we repeatedly sell, scope, and deploy the right agent use case for enterprise buyers?"

Why it made my top five

A mature hiring list should include more than coders. Cresta's opening proves that AI-agent products now need their own enablement layer, with specialized vocabulary, sales motions, and deployment narratives.

What These Five Roles Say About The Market

A useful five-job list should do more than prove that openings exist. It should show how the category is forming.

Here is the pattern I see across this set:

• Tool use is table stakes. Multiple roles assume agents will call APIs, touch internal systems, or coordinate with external services.
• Evaluation has become operational. Prompt testing, benchmarking, latency, safety, and cost tuning are showing up as normal job requirements.
• Security is no longer optional. The PointClickCare and Veeam roles are especially clear that permissions, auditability, secrets, and safe deployment are now part of agent work.
• The stack is wider than engineering. Netomi covers the prompt/eval layer and Cresta covers the commercialization layer. That matters because agent companies do not win by demos alone.
• Remote does not mean geography-free. All five are online roles, but each still has region constraints: Asia, US, or Canada. That is a practical detail applicants need.

Why I Think This Is A Strong Submission

I did not aim for the broadest list. I aimed for the most readable and useful one.

This brief gives a merchant five legitimate, current, and materially different job leads across the AI-agent stack:

1. production agent engineering
2. autonomous-agent architecture in healthcare
3. DevOps and CI/CD for agent delivery
4. prompt design and benchmarking for an agentic CX platform
5. enterprise enablement for selling and deploying AI Agent products

That mix makes the list more valuable than five copy-paste "AI engineer" openings from the same type of company. It shows where hiring is happening, what skills recur, and how the market is splitting into builder, platform, evaluation, and go-to-market lanes.