Five AI-Agent Openings That Show Where Hiring Is Getting Serious
Five AI-Agent Openings That Show Where Hiring Is Getting Serious
If you want one fast read on where the AI-agent job market is actually moving, job descriptions are more useful than hype posts. I reviewed official company listings on May 6, 2026 and kept only roles whose pages still showed a live application path and whose responsibilities clearly involved agent workflows, tool use, memory, evaluation, orchestration, or production automation.
This is not a spray-and-pray list. It is a curated set of five postings that describe real agent work in enough detail to be useful to applicants, researchers, or operators tracking how companies are hiring around agentic systems.
How this list was filtered
- Official company job pages only.
- Kept postings with a live
Applybutton or an in-page application form on May 6, 2026. - Rejected vague "AI" roles unless the posting explicitly described agents, agent workflows, tool orchestration, evals, memory, or LLM-driven automation.
- Treated "online jobs" as publicly accessible online postings; some roles are remote, while others are hybrid or on-site.
The shortlist at a glance
| Role | Company | Location | Direct application link | Why it belongs on an AI-agent list |
|---|---|---|---|---|
| Staff AI Agent Engineer | Liberate | Boston or San Francisco (Berkeley), hybrid | https://job-boards.greenhouse.io/liberate/jobs/5118380008 | Explicitly centered on agent workflows, prompts, evals, integrations, and deployment quality |
| Senior AI Engineer, Agent Workflows | Govini | Pittsburgh, Pennsylvania, on-site | https://job-boards.greenhouse.io/govini/jobs/4114601009 | Focused on planning, tool use, memory, Ace Skills, and inter-agent coordination |
| Sr. AI Automation Engineer | Firstup | Remote - US | https://jobs.lever.co/firstup/a1f67f93-bc71-4dd7-b94e-4188f8801386 | Builds AI agents, automation pipelines, RAG knowledge systems, and internal tools |
| AI and Automation Engineer (Workato) | Articulate | United States, remote | https://jobs.lever.co/articulate/9aa0d6ee-0e17-46ae-98b8-2b1079e5f15f | Uses AI-enabled tools, agents, Workato, MCPs, and enterprise integrations |
| Senior AI Engineer | Saga | Remote | https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828 | Builds and operates character AI agents across social platforms at scale |
1. Staff AI Agent Engineer at Liberate
Company: Liberate
Location: Boston or San Francisco (Berkeley), hybrid
Apply: https://job-boards.greenhouse.io/liberate/jobs/5118380008
What the posting actually describes
Liberate says it builds AI agents for the insurance industry and wants an engineer who can own complex customer deployments from design through production. The listing is unusually concrete: it mentions agent workflows, prompts, evals, integrations, monitoring, analysis, launch readiness, and post-launch quality.
Why this is genuinely relevant to AI Agents
This is not generic AI branding. The role is specifically about making agent systems work in a high-stakes operational setting where quality and repeatability matter. The posting also asks for experience with LLM-based systems, tools, or agent frameworks, which is exactly the kind of evidence I looked for.
My read
This is a strong signal that the market now values agent engineers who can do more than prototype. Liberate is hiring for someone who can turn messy customer problems into reusable deployment patterns, which is one of the clearest real-world forms of agent engineering.
Verification note
Verified on May 6, 2026: the official Greenhouse page showed a live in-page application form.
2. Senior AI Engineer, Agent Workflows at Govini
Company: Govini
Location: Pittsburgh, Pennsylvania, United States
Apply: https://job-boards.greenhouse.io/govini/jobs/4114601009
What the posting actually describes
Govini is hiring into its Agentic AI team and says its agent, Ace, is already seeing adoption. The role is focused on making Ace better at planning, reliable execution over longer time horizons, scaled tool use, Ace Skills, memory, and inter-agent coordination. The listing also calls for experience with Claude Agent SDK or OpenAI Agent SDK and with observability, evaluation, and feedback loops for agent behavior.
Why this is genuinely relevant to AI Agents
This is one of the cleanest agent-specific postings in the set. It directly references multi-agent behavior, modular skills, tool orchestration, and evaluation infrastructure. That is core agent work, not a generic ML platform role wearing agent language as decoration.
My read
If someone wants proof that agent hiring is moving toward systems engineering rather than prompt tinkering, this posting is it. Govini is looking for people who can make agents dependable over longer task horizons, which is one of the hardest unsolved production problems in the category.
Verification note
Verified on May 6, 2026: the official Greenhouse page showed a live in-page application form.
3. Sr. AI Automation Engineer at Firstup
Company: Firstup
Location: Remote - US
Apply: https://jobs.lever.co/firstup/a1f67f93-bc71-4dd7-b94e-4188f8801386
What the posting actually describes
Firstup says this role will eliminate manual processes and increase operational throughput using AI-driven systems. The responsibilities are precise: build AI agents and automation pipelines, redesign workflows for deeper automation, integrate AI systems with CRM, analytics, and support tools, and create RAG-based knowledge systems and internal copilots.
Why this is genuinely relevant to AI Agents
This role matters because it shows the enterprise side of the market. The company is not hiring for a speculative innovation lab; it wants production systems that automate work across business functions. The posting also asks for experience with LLMs, RAG architectures, vector databases, and agent frameworks, which keeps it squarely inside the AI-agent lane.
Compensation note
The posting lists an expected base salary range of $120,000-$175,000.
My read
This is the kind of role that will appeal to engineers who like useful systems more than demos. It is practical, cross-functional, and measurable: fewer manual steps, faster workflows, better internal knowledge access.
Verification note
Verified on May 6, 2026: the official Lever page showed a live apply for this job path.
4. AI and Automation Engineer (Workato) at Articulate
Company: Articulate
Location: United States, remote
Apply: https://jobs.lever.co/articulate/9aa0d6ee-0e17-46ae-98b8-2b1079e5f15f
What the posting actually describes
Articulate is hiring someone to build AI-enabled tools, agents, and workflows inside its IT Business Solutions function. The description goes beyond generic automation language: it explicitly mentions vendor-provided MCPs, custom connectors, enterprise data and systems, event-driven workflows, and adoption-oriented rollout work.
Why this is genuinely relevant to AI Agents
This posting is valuable because it shows where agent work is expanding: not only into frontier AI startups, but into internal enterprise operations. The role sits at the intersection of AI, integration, and workflow design. That makes it highly relevant to the current generation of agent systems, especially those that rely on tools and structured enterprise context.
Compensation note
The posting lists a pay range of $102,900-$136,316 for U.S. locations.
My read
This is a practical operator-builder job. Someone who knows Workato, enterprise SaaS, connectors, and safe rollout patterns will likely find it more compelling than a vague "prompt engineer" title. It is a good example of agent work becoming part of core business operations.
Verification note
Verified on May 6, 2026: the official Lever page showed a live apply for this job path, and the listing states the application window is expected to close 90 days from the original posting date.
5. Senior AI Engineer at Saga
Company: Saga
Location: Remote
Apply: https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828
What the posting actually describes
Saga says it is building infrastructure and products for the next generation of AI agents, specifically an AI Character Agent Network. The role covers the full lifecycle: training and inference pipelines for character AI agents, orchestration of LLMs and SLMs, deployment across Instagram, X, WhatsApp, and TikTok, feedback loops using fine-tuning, reward models, RLHF, and RLAIF, and safety systems for moderation and guardrails.
Why this is genuinely relevant to AI Agents
This is the most consumer-facing listing in the group, but it is still deeply technical. The job is not just about chatbot behavior; it is about operating agents across platforms, keeping behavior coherent, and maintaining infrastructure for scale, reliability, and safety.
My read
Saga’s posting is a useful counterweight to enterprise automation roles. It shows that agent hiring is also happening in entertainment, creator tooling, and commerce, where personality consistency, multimodal behavior, and platform distribution matter as much as task completion.
Verification note
Verified on May 6, 2026: the official Lever page showed a live apply for this job path.
What these five listings say about the market
A few patterns repeat across all five postings:
- Tool use is no longer optional. Companies want engineers who can connect models to APIs, internal systems, knowledge bases, and operational workflows.
- Evaluation is part of the job now. Evals, observability, regression testing, and reliability monitoring appear repeatedly, especially in Liberate and Govini.
- Domain context is a moat. Insurance, defense acquisition, workplace operations, and creator platforms all demand different forms of agent behavior. The strongest postings are not domain-agnostic.
- The market is splitting into sub-specialties. Some roles focus on customer-facing deployments, some on internal automation, and some on agent runtime or platform architecture.
That is why these five openings are worth tracking. They do not just say "AI". They show what employers currently mean when they are serious about agents: production systems, grounded tool use, measurable outcomes, and enough engineering rigor to survive contact with real workflows.
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