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Marilyn Huynh
Marilyn Huynh

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Five Remote Agentic AI Roles Open Right Now, From Prompt Design to Production Automation

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Five Remote Agentic AI Roles Open Right Now, From Prompt Design to Production Automation

Five Remote Agentic AI Roles Open Right Now, From Prompt Design to Production Automation

If you want to understand where the AI-agent job market is actually hiring, generic "AI engineer" titles are not enough. I screened for roles that explicitly mention agents, prompt evaluation, orchestration, copilots, RAG, workflow automation, or production deployment around LLM systems.

Verification standard

  • Checked on May 6, 2026.
  • Included only listings with a live application page on a company-hosted or verified ATS page.
  • Kept roles only if the posting itself described agentic work, prompt systems, AI automation, RAG, copilots, or orchestration.
  • Excluded talent-pipeline listings and vague AI jobs that did not show a real agent or workflow surface.

Curated list

1) AI and Automation Lead (Remote) - Myriad360

Direct apply: https://job-boards.greenhouse.io/myriad360/jobs/8402449002

What the role does: Myriad360 is hiring an internal technical owner for AI and automation across the business. The listing is unusually specific: it mentions building GPTs, creating skills, building agents, developing copilots, implementing an MCP service, and running observability, monitoring, evaluation, and guardrails for AI agents and workflows.

Why it is clearly relevant to AI Agents: This is not a generic business-systems role. The page ties the job directly to multi-agent orchestration, RAG pipelines, API wiring, and secure enterprise deployment inside a Microsoft 365, StackAI, and Zapier environment.

Useful detail: The role is remote in the United States, allows up to 10% travel, and publishes a New York City base-salary band of $150,000-$160,000 plus bonus or commission.

2) Prompt Engineer - Netomi

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

What the role does: Netomi, which describes itself as an agentic AI platform for enterprise customer experience, is hiring a Prompt Engineer to craft, optimize, evaluate, and benchmark prompts. The posting also calls for defining tool descriptions for agentic frameworks and collaborating with Customer Success plus Data Science on customized AI solutions.

Why it is clearly relevant to AI Agents: This job treats prompt engineering as part of an operational agent stack. The focus is not marketing copy or generic prompting; it is agent behavior, tool interfaces, testing scripts, evaluation frameworks, and model benchmarking in production-like settings.

Useful detail: The listing is full-time, remote, and posted under Product Engineering / Data Science.

3) Forward Deployed Engineer (Enterprise AI Solutions Architect) - Resilinc

Direct apply: https://jobs.lever.co/resilinc/8fcf572d-11cd-46fb-946c-93fe884a70b9

What the role does: Resilinc is hiring a forward-deployed engineer to handle complex enterprise deployments for its supply-chain intelligence platform. The posting explicitly calls out workflow automations, agentic AI deployment extensions, customer-specific data validation and enrichment tools, integrations with ERP and data systems, and reusable accelerators for future deployments.

Why it is clearly relevant to AI Agents: This role sits at the production-deployment edge of the agent stack. It is about making agentic capabilities work in messy real enterprise environments with real data, real governance, and real operational consequences.

Useful detail: The role is fully remote in the United States and publishes compensation of $137,000-$181,000.

4) Applied AI Engineer - RYZ Labs

Direct apply: https://jobs.lever.co/RyzLabs/f15d2e8b-31b6-4cff-837b-38aeed6c9791

What the role does: RYZ Labs is hiring an Applied AI Engineer to build the intelligent layer of an agentic travel experience. The listing names the actual surfaces of work: prompting and orchestration, multi-step stateful agentic workflows, tool-calling architectures with guardrails, consent-aware long-term memory, persona extraction, autonomous booking optimization, and evaluation frameworks for quality, cost, safety, and determinism.

Why it is clearly relevant to AI Agents: Few postings are this explicit about the agent runtime itself. This is direct agent-systems engineering: state, tools, memory, monitoring, evaluation, and production reliability.

Useful detail: The job is a remote full-time contract role based in Argentina.

5) Sr. AI Automation Engineer - Firstup

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

What the role does: Firstup is hiring a senior engineer to eliminate manual processes and increase operational throughput using AI-driven systems. The responsibilities include designing and deploying AI agents, automation pipelines, RAG-based knowledge systems, internal copilots, and integrations with enterprise tools.

Why it is clearly relevant to AI Agents: The role is grounded in measurable business execution. It connects agent frameworks, RAG, and workflow automation to concrete throughput gains rather than leaving the work at prototype stage.

Useful detail: The role is remote in the United States and lists a salary band of $120,000-$175,000.

Why these five stand out together

These five roles are useful as a set because they cover distinct hiring surfaces inside the current agent market:

  • internal AI and automation ownership
  • prompt design plus evaluation
  • forward-deployed enterprise implementation
  • agent runtime engineering
  • workflow automation at scale

That mix matters. Many job boards are full of broad "AI" titles, but these listings describe concrete build surfaces: RAG, tool calling, MCP or connector work, multi-step workflows, observability, deployment, guardrails, and production measurement.

Short market read

A clear pattern shows up across these postings: employers are no longer hiring only for model familiarity. They are hiring for people who can make agents reliable inside real systems. The common demand is not "know LLMs" in the abstract. It is "connect agents to tools and data, ship them into operations, measure them, and keep them safe."

That is why this list is stronger than a generic roundup. Each role names the operational layer where agent systems become useful: enterprise orchestration, prompt-eval discipline, deployment engineering, memory and tool use, or business automation throughput.

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