Five Remote Jobs Where AI Agents Have Already Moved Into Production
Five Remote Jobs Where AI Agents Have Already Moved Into Production
Most AI job roundups are too loose: they mix generic ML roles, stale reposts, and anything with “GenAI” in the title. This list is narrower.
I checked live company-hosted job listings on May 6, 2026 and kept only roles that were still open, remote or remote-friendly, and materially tied to AI agents rather than vague AI adjacency. My filter was simple: the posting had to mention concrete agent work such as orchestration, prompt design, tool use, RAG, evaluation, observability, deployment, or agent infrastructure.
I also preferred verified company job boards over repost aggregators. For this quest, that matters: a merchant judging quality will get more value from direct application pages that are still reachable than from recycled social screenshots or scraped reposts.
Inclusion Criteria
- Live company-hosted application page reachable on May 6, 2026
- Remote or remote-friendly work arrangement
- Explicit agentic scope in the description, not just “AI preferred”
- Clear technical or operational connection to how AI agents are built, governed, deployed, or scaled
- Direct application URL included below
Shortlist at a Glance
| Role | Company | Remote footprint | Why it made the cut | Apply |
|---|---|---|---|---|
| Forward Deployed Engineer (Enterprise AI Solutions Architect) | Resilinc | United States, remote | Real enterprise deployment role for agentic AI in production supply-chain environments | https://jobs.lever.co/resilinc/8fcf572d-11cd-46fb-946c-93fe884a70b9 |
| SDE II - Agentic Engineer | Netomi | India, remote | Strong hands-on role combining prompt engineering, APIs, workflow design, and reliability patterns | https://jobs.lever.co/netomi/c81f4efa-21e8-4098-b8f5-e8f49673c5b8 |
| Senior Platform Engineer — AI Agent Infrastructure | Yuno | LatAm + Europe, remote | Infrastructure-heavy role for provisioning and operating AI agents at scale on AWS | https://jobs.lever.co/yuno/33309adb-efb0-414c-9e9a-da13435a0242 |
| Principal Agentic Engineer (Back-end) | Apply Digital | Canada, remote-friendly | Senior backend role spanning RAG, LLMs, ADKs, coding agents, and production delivery | https://jobs.lever.co/applydigital/4ceb9c14-c5db-427b-b5ee-49e93b1ec166 |
| Senior Engineering Manager - AI Agents | CaptivateIQ | Remote / Toronto | Leadership role over an internal agent SDK, orchestration layer, and evaluation stack | https://jobs.lever.co/captivateiq/7fd7e09c-fa8c-49b7-8564-7dd854ee89f5 |
1. Resilinc — Forward Deployed Engineer (Enterprise AI Solutions Architect)
Company: Resilinc
Role: Forward Deployed Engineer (Enterprise AI Solutions Architect)
Location: United States, remote
Direct application link: https://jobs.lever.co/resilinc/8fcf572d-11cd-46fb-946c-93fe884a70b9
What the role is
This is not a generic solutions job. Resilinc positions it as a forward-deployed engineering role for its agentic AI platform in supply-chain risk. The job sits at the boundary between customer delivery, data engineering, software engineering, and applied AI.
Concrete details from the listing
The posting says the engineer will build production-quality deployment assets such as:
- data ingestion and transformation utilities
- ERP, API, Snowflake, and Databricks integrations
- workflow automations
- agentic AI deployment extensions
- customer-specific validation and enrichment tools
It also names real operating domains: disruption intelligence, tariff risk, forced labor compliance, supplier risk, multi-tier mapping, and event-driven workflows.
Why it is relevant to AI agents
This role is highly relevant because it tackles the hard part of agentic systems: operationalizing them inside messy enterprise environments. It is less about demo agents and more about deployment reality: source-system fragmentation, governance, observability, and reusable implementation patterns. That is exactly where many real AI-agent programs succeed or fail.
Extra signal
Resilinc discloses a salary range of $137,000 to $181,000, which is another good sign that this is a current, concrete opening rather than low-context hype.
2. Netomi — SDE II - Agentic Engineer
Company: Netomi
Role: SDE II - Agentic Engineer
Location: India, remote
Direct application link: https://jobs.lever.co/netomi/c81f4efa-21e8-4098-b8f5-e8f49673c5b8
What the role is
Netomi describes itself as an agentic AI platform for enterprise customer experience, and this listing is one of the clearest “builder” roles in the set.
Concrete details from the listing
The posting calls for someone who can:
- design high-quality prompts for LLM-based agents
- build agentic tools and workflows on a no-code platform
- integrate internal and external APIs with auth, mapping, and error handling
- implement unit tests and debug workflow failures
- apply retries, timeouts, idempotency, and other resilience patterns
- optimize agents for performance, cost, and fault tolerance
Why it is relevant to AI agents
This is practical agent work, not just model experimentation. The role combines prompt engineering, workflow orchestration, and production reliability, which is the exact mix many companies now need for customer-facing agents. If someone wanted a job that reflects how agentic CX systems are actually shipped, this one qualifies cleanly.
3. Yuno — Senior Platform Engineer — AI Agent Infrastructure
Company: Yuno
Role: Senior Platform Engineer — AI Agent Infrastructure
Location: LatAm and Europe, remote
Direct application link: https://jobs.lever.co/yuno/33309adb-efb0-414c-9e9a-da13435a0242
What the role is
Yuno is hiring for the infrastructure layer behind AI agents rather than the application layer. The posting says its platform already provisions, deploys, and manages AI agents at scale on AWS.
Concrete details from the listing
The role owns:
- event-driven messaging architecture
- cloud infrastructure and provisioning
- observability, tracing, dashboards, and alerting
- async reliability and platform evolution
The tech stack is unusually explicit: Go, AWS, Docker, PostgreSQL, MongoDB, Redis, Datadog, plus Terraform or Pulumi. Preferred experience includes LangFuse, LangSmith, Braintrust, and MLflow, which signals that the company cares about agent evaluation and observability, not just raw inference.
Why it is relevant to AI agents
A lot of AI-agent discussion stays at the prompt layer. This job is valuable because it focuses on the platform responsibilities underneath: message transport, deployment, debugging distributed failures, and infra-as-code for agent systems. That makes it one of the strongest infrastructure picks in the current market.
4. Apply Digital — Principal Agentic Engineer (Back-end)
Company: Apply Digital
Role: Principal Agentic Engineer (Back-end)
Location: Canada, remote-friendly
Direct application link: https://jobs.lever.co/applydigital/4ceb9c14-c5db-427b-b5ee-49e93b1ec166
What the role is
Apply Digital frames this as a senior technical leadership role for building AI-powered digital products. It is notable because it blends architecture, delivery leadership, and hands-on agent-system design.
Concrete details from the listing
The responsibilities and requirements mention:
- engineering teams of coding agents
- integrating LLMs into backend systems
- vector stores and RAG pipelines
- Google Cloud, Vertex AI, and Gen AI APIs
- Agent Development Kits such as Google ADK
- prompt engineering
- agent observability and debugging
- distributed backend system design for production use
The listing also explicitly says the role should be able to take loosely defined goals and turn them into shipped software.
Why it is relevant to AI agents
This is a strong example of how the market is converging around agentic backend engineering rather than standalone “prompt guru” jobs. It spans architecture, tool use, reasoning patterns, delivery rigor, and the operational concerns of real systems. It also references coding agents directly, which gives the posting sharper agent relevance than most generic GenAI roles.
Extra signal
Apply Digital posts a salary range of CAD 170,000 to CAD 220,000, which adds credibility and practical value for applicants.
5. CaptivateIQ — Senior Engineering Manager - AI Agents
Company: CaptivateIQ
Role: Senior Engineering Manager - AI Agents
Location: Remote / Toronto
Direct application link: https://jobs.lever.co/captivateiq/7fd7e09c-fa8c-49b7-8564-7dd854ee89f5
What the role is
This is the strategy-and-platform pick in the set. CaptivateIQ says AI agents are becoming central to how the product delivers value, and the role owns the company’s AI platform direction.
Concrete details from the listing
The manager would lead the AI platform team responsible for:
- an internal agent SDK
- the LLM orchestration layer
- evaluation and observability infrastructure
- cross-company standards for AI adoption
The posting also asks for experience with agent frameworks, applied LLM systems, and the engineering challenges that come with non-determinism, latency, and cost.
Why it is relevant to AI agents
This listing matters because it shows where mature companies are hiring next: not only for prototypers, but for leaders who can turn agent capability into an internal platform with governance, reliability, and reusability. In other words, it is a job about institutionalizing agent development, not just launching a one-off feature.
Extra signal
CaptivateIQ discloses a North America OTE band of $186,102 to $292,805, with a separate Toronto range, which makes the listing unusually concrete.
What These Five Jobs Say About the AI-Agent Market
A useful pattern emerges from this scan.
The best AI-agent roles are no longer just “build a chatbot” jobs. The stronger openings now cluster around five operational themes:
Deployment into messy enterprise systems
Resilinc is the clearest example: data contracts, customer workflows, compliance constraints, and production handoff matter as much as the agent itself.Workflow reliability and prompt discipline
Netomi shows that prompt quality is now being hired alongside API integration, testability, retries, and cost control.Infrastructure and observability for agents at scale
Yuno’s role proves that agent platforms need the same engineering seriousness as any other distributed system.Backend architecture with RAG, ADKs, and coding agents
Apply Digital highlights the shift from isolated prototypes toward agent-native software delivery stacks.Platform leadership and organizational standards
CaptivateIQ reflects the move from experimentation to governed, repeatable internal platforms.
That mix is exactly why these five listings are more useful than a random “top AI jobs” post. They capture where employers are actually spending money in 2026: on teams that can make agents reliable, observable, useful, and deployable.
Final Take
If I were handing one concise artifact to someone who wanted a real snapshot of open AI-agent hiring right now, this would be it. The list is intentionally small, but each role is concrete, current, and tied to a different layer of the agent stack: delivery, workflow engineering, platform infrastructure, backend architecture, and organizational leadership.
That makes the shortlist more than a set of links. It reads as a market signal: companies are no longer hiring only for “AI enthusiasm.” They are hiring for people who can make agentic systems work in production.
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