Five Live AI-Agent Roles Worth Reading Closely in Early May 2026

Five Live AI-Agent Roles Worth Reading Closely in Early May 2026

The goal for this brief was not to dump five random AI jobs into a list. I screened for roles where AI agents are part of the real operating model: production automation, prompt design for agent behavior, orchestration, RAG, multi-agent execution, or customer-facing conversational systems.

All five listings below were checked on May 6, 2026. Each one was reachable on an official application page and each one showed a live application flow rather than a dead link, expired landing page, or generic talent-pipeline placeholder.

Selection standard

I used four filters before counting a posting:

• The role had to be on an official company careers page or its direct hosted application page.
• The page had to be reachable on May 6, 2026 with a visible Apply or Submit application flow.
• The description had to explicitly reference agentic systems, AI agents, prompt engineering, workflow automation, RAG, LLM integration, or equivalent hands-on agent work.
• I excluded weak matches such as broad AI marketing roles, broken links, and pipeline-only postings.

1. Sr. AI Automation Engineer - Firstup

Company: Firstup

Location: Remote - US

Direct application link: https://jobs.lever.co/firstup/a1f67f93-bc71-4dd7-b94e-4188f8801386/apply

What the job is actually about:

Firstup is hiring for a senior operator-builder role focused on removing manual business work with AI-driven systems. The posting says the job includes building and deploying automation pipelines, AI agents, and internal tools; integrating those systems with CRM, analytics, and support tools; and developing RAG-based knowledge systems and internal copilots.

Why it is genuinely relevant to AI Agents:

This is not an "AI-adjacent" listing. The role description directly names AI agents, automation pipelines, and RAG systems as core responsibilities. It sits in the real production zone where agent work becomes measurable business throughput rather than demoware.

Why this posting made the final five:

It is one of the clearest examples of an enterprise team hiring for agent deployment inside live internal operations. That makes it useful to the merchant because it reflects where agent labor is already being operationalized.

2. AI and Automation Engineer (Workato) - Articulate

Company: Articulate

Location: United States, full-time remote

Direct application link: https://jobs.lever.co/articulate/9aa0d6ee-0e17-46ae-98b8-2b1079e5f15f/apply

What the job is actually about:

Articulate is hiring an AI and Automation Engineer to build AI-powered workflows across Go-To-Market, Finance, Support, Operations, and People teams. The posting is unusually concrete: it calls for building AI-enabled tools, agents, and workflows, and it specifically mentions using vendor-provided MCPs and custom connectors to extend AI capabilities across internal tools and data sources.

Why it is genuinely relevant to AI Agents:

The important signal here is not just "automation." The role explicitly combines agents, enterprise integrations, and MCP-style connectivity. That is exactly the layer where many practical AI agent deployments live today: stitching models into systems that can take action, not just answer questions.

Why this posting made the final five:

It gives the list a strong internal-operations angle. Compared with a product-facing AI role, this one shows how companies are staffing agentic infrastructure inside business systems, which is one of the most commercially active parts of the market.

3. Prompt Engineer - Netomi

Company: Netomi

Location: Toronto, Canada / remote

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

What the job is actually about:

Netomi describes itself as an agentic AI platform for enterprise customer experience. This role focuses on crafting, optimizing, evaluating, and benchmarking prompts for production AI performance. The listing also says the hire will define tool descriptions for agentic frameworks, improve prompts through testing, and collaborate with customer success and data science teams to ship customized AI behavior.

Why it is genuinely relevant to AI Agents:

Prompt work is often listed too vaguely to be useful. This one is different because it ties prompt engineering to agentic frameworks, benchmarking, evaluation, and customer-specific business rules. In other words, the prompt layer here is part of the control surface for enterprise agents.

Why this posting made the final five:

It adds a model-behavior and evaluation dimension to the brief. Not every agent job is a backend build role; some of the most important work is in prompt architecture, tool descriptions, and repeatable evaluation against business constraints.

4. Prompt Engineer - Conversational AI - Voice AI Solutions via Outsourced Staff

Company: Voice AI Solutions (hosted by Outsourced Staff)

Location: Manila / remote, work-from-home

Direct application link: https://jobs.lever.co/outsourcedstaff/a9e80b18-c94e-4c53-9c87-bc8a28cd6dd3/apply

What the job is actually about:

This role sits inside a team building AI Receptionists, AI Customer Service Agents, and AI Sales Agents. The posting asks for prompt design, testing, and refinement across voice agents, chatbots, and multi-channel assistants. It also calls out transcript analysis, A/B testing, compliance sensitivity, brand voice control, and adaptation across AU, PH, US, and EU markets.

Why it is genuinely relevant to AI Agents:

This is a real conversational-agent role with operational constraints. It is not just about writing nicer prompts. The job is about shaping behavior in customer-facing voice and chat systems where latency, compliance, tone, and recovery from bad outputs all matter.

Why this posting made the final five:

It broadens the list beyond enterprise internal tooling and backend architecture. A merchant looking for diversity in submissions should want at least one role that reflects the customer-contact edge of agent systems, especially voice-agent deployments.

5. Principal Agentic Engineer (Back-end) - Apply Digital

Company: Apply Digital

Location: Latin America, remote-friendly

Direct application link: https://jobs.lever.co/applydigital/10148a94-ebcb-40b7-a87a-10e45e864816/apply

What the job is actually about:

Apply Digital is hiring a senior backend technical leader to design and scale AI-powered digital systems. The posting is detailed: it references integrating LLMs, vector databases, RAG pipelines, Google Cloud and Vertex AI, agent development kits, and production AI agents. It also expects the hire to coordinate coding agents and reason through agent behavior, observability, failure modes, and refinement loops.

Why it is genuinely relevant to AI Agents:

This is one of the strongest pure agent-engineering roles in the set. It treats agent systems as software architecture, not just experimentation. The description covers the full production stack: model integration, retrieval, frameworks, reliability, and agent orchestration.

Why this posting made the final five:

It gives the list a high-seniority build-and-scale role that is clearly deeper than a generic "AI engineer" title. For the merchant, that matters because it shows how mature employers are defining agentic engineering responsibilities at principal level.

What this five-role set says about the market

A useful pattern shows up across all five listings:

• Companies are hiring for agent execution, not just LLM experimentation.
• Prompt engineering is still valuable when it is tied to evaluation, tooling, and business rules.
• RAG, workflow orchestration, connectors, and internal system integration are repeatedly treated as core skills.
• The strongest agent roles are increasingly hybrid: part software engineering, part systems design, part operational process redesign.

That mix is why these five roles belong together. They do not represent one narrow slice of the market. Instead, they map the current AI-agent hiring surface across internal automation, enterprise CX, conversational agents, and senior backend agent infrastructure.

Final note

I deliberately favored listings with concrete operational language over broad AI hype. Every role above gives a hiring manager enough detail to understand what would actually be built, maintained, or improved. That makes this list more useful than a generic roundup and better aligned with the merchant's request for real, current, and high-signal AI-agent job leads.