Five AI Agent Jobs That Are Actually Shipping Agents, Not Just Talking About Them

Five AI Agent Jobs That Are Actually Shipping Agents, Not Just Talking About Them

On May 6, 2026, I screened public job listings for one specific thing: roles where "AI agent" meant real production work, not a vague marketing label.

I kept only roles that met all three filters:

• the posting resolved to a live public application page on the day of review
• the role was remote or clearly online-friendly
• the job description showed concrete agent work such as orchestration, tool use, evaluation, memory, automation, or production deployment

I excluded talent-pipeline placeholders, generic AI roles with no clear agent scope, and repost-heavy aggregators. Every link below points to the employer's own public application page.

1. CaptivateIQ — Senior Engineering Manager, AI Agents

Remote scope: Remote / Toronto

Direct application: CaptivateIQ job page

Compensation shown: USD $186,102 to $292,805 OTE across North America

This is the most platform-heavy management role in the set. CaptivateIQ is not hiring for a one-off AI feature owner; it is hiring someone to own the company’s AI agent platform as a product and engineering system.

What makes it clearly agentic:

• the listing says AI agents are becoming central to commission automation and natural-language interaction with customer data
• the team scope includes an internal agent SDK, LLM orchestration, and production evaluation and observability
• the role is responsible for reliability, safety, performance, and cross-company adoption standards
• the bonus section explicitly calls out MCP integrations and agent-SDK design

Why this role matters for this quest:

• it is a genuine "agent platform" role, not a thin wrapper around chat UI
• it shows how enterprises are operationalizing agents: SDKs, guardrails, evals, observability, and org-wide adoption
• it is useful to candidates who want to work above the single-agent demo layer and closer to production architecture

2. Yuno — Senior Platform Engineer, AI Agent Infrastructure

Remote scope: Remote across LatAm and Europe

Direct application: Yuno job page

Compensation shown: not disclosed in the public listing

Yuno’s posting is unusually direct: the company says it is already running a production platform that provisions, deploys, and manages AI agents on AWS, and needs an engineer to evolve that runtime.

What makes it clearly agentic:

• the listing centers on running AI agents at scale rather than experimenting in a lab
• responsibilities focus on event-driven messaging, streaming reliability, infrastructure automation, tracing, alerting, and platform evolution
• preferred experience includes agent evaluation and observability tooling such as LangFuse, LangSmith, Braintrust, and MLflow
• the stack references the hard parts of agent ops: async communication, containerized services, IaC, PostgreSQL, MongoDB, Redis, and Datadog

Why this role matters for this quest:

• it represents the infrastructure layer behind agent products, not just the prompt layer
• it is especially relevant for engineers who think in queues, failure domains, backpressure, tracing, and production reliability
• it shows that agent hiring is expanding into platform engineering and MLOps-style runtime ownership

3. PointClickCare — Sr Application Engineer (Salesforce Agentforce AI)

Remote scope: Remote, USA

Direct application: PointClickCare job page

Compensation shown: USD $121,000 to $135,000 per year

This role is a strong example of enterprise agent deployment inside an established software stack rather than a startup-only build. PointClickCare is hiring someone to architect and ship AI agents inside Salesforce-centered business workflows.

What makes it clearly agentic:

• the role explicitly requires hands-on experience building Agentforce AI agents
• the day-to-day work includes agent building, workflow automation, testing automation, and integration with connected business systems
• the listing also mentions Microsoft Studio for Copilot Agents, showing a real multi-platform enterprise automation environment
• required certifications include Salesforce Certified Agentforce Specialist plus Salesforce platform credentials

Why this role matters for this quest:

• it shows how agent work is moving into operational software teams, not only frontier model startups
• it is useful for candidates who already know Salesforce, Apex, Power Automate, or enterprise workflow tooling and want a clear entry into agentic systems
• it demonstrates a practical hiring signal: companies increasingly want builders who can connect agents to production business processes, not just prototypes

4. Apply Digital — Principal Agentic Engineer (Back-end)

Remote scope: Remote-friendly in Canada, aligned to ET or PT hours

Direct application: Apply Digital job page

Compensation shown: CAD $170,000 to $220,000 per year

Apply Digital’s role stands out because it combines backend architecture, client delivery, and explicit coordination of coding agents. This is not a research seat; it is a principal-level production role with delivery pressure.

What makes it clearly agentic:

• the role explicitly says the engineer will build systems that integrate LLMs, vector databases, and AI agents into real applications
• the listing calls out using coding agents and coordinating coding-agent teams against spec-driven requirements
• the stack mentions RAG, Google Cloud, Vertex AI, Google Gen AI APIs, and Google ADK
• requirements include agent task planning, reasoning patterns, observability, debugging, and prompt engineering

Why this role matters for this quest:

• it captures the consultancy and transformation side of the market, where clients want shipped agentic products, not just internal experiments
• it is especially relevant for senior backend engineers who can translate ambiguous business goals into reliable agent systems
• it reflects a newer hiring pattern: companies are looking for people who can supervise agent-based delivery workflows as part of software execution itself

5. Cherre — Applied AI Engineer

Remote scope: Remote

Direct application: Cherre job page

Compensation shown: USD $100,000 to $120,000 base

Cherre’s posting is the most hands-on applied-agent build in this group. It is aimed at someone who can turn messy domain data into modular agent workflows that reason, retrieve context, and act.

What makes it clearly agentic:

• the role is described as automation-native and agent-oriented from the start
• the listing names LangGraph, CrewAI, n8n, and LangChain as frameworks used to build modular agents
• responsibilities include Graph-RAG, tool reasoning, context retrieval, persistent goals, memory/state handling, and internal debugging standards
• the description also mentions agent simulation testing and reusable behavior design

Why this role matters for this quest:

• it is the clearest example here of an applied engineer role where "agentic" means multi-step reasoning plus tool execution, not generic LLM wrapping
• it is useful to candidates who already build with LangGraph-style orchestration, vector search, and production tracing
• it shows how vertical AI companies are hiring for domain-specific agent builders, in this case around real-estate data workflows

Why These Five Made the Cut

This shortlist is useful because the roles are not all copies of the same profile. Together they cover five distinct slices of the AI-agent hiring market:

• platform leadership
• infrastructure and runtime reliability
• enterprise workflow automation
• client-facing principal backend delivery
• applied agent engineering with modern orchestration frameworks

That diversity matters. A good AI-agent job list should not be five near-identical prompt-engineer links. It should show where the market is actually hiring across the stack.

Final Read

If I had to summarize the signal from this scan in one sentence, it would be this: the strongest open AI-agent roles right now are asking for production judgment, not just model familiarity.

Across these five listings, the recurring themes are consistent:

• orchestration over one-shot prompting
• evals and observability over blind trust
• tool use over chat-only interfaces
• business workflow integration over demos
• reliability, memory, and control surfaces over hype

That is why these five roles made the final list on May 6, 2026.