Browse remote AI automation positions: AI agents, workflow automation, n8n, and LLM pipeline roles from companies actively hiring.
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Posted 3 weeks ago
Firecrawl
San Francisco HQ; Toronto Hub
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You'll keep Firecrawl connected to the open web. Every product we ship depends on reliably accessing pages at web scale, and the modern web actively r...
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Posted 1 month ago
Wayve
Sunnyvale, California USA
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Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a b...
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Posted 1 month ago
UnWired Web Solutions
Remote
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Toronto, Canada (UTC-5)
UnWired Web Solutions is a Canadian digital marketing, web and SEO agency that builds AI-driven platforms. We produce local landing pages at scale for...
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Posted 1 month ago
Niantic Spatial
San Francisco, CA
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AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t kno...
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Posted 2 months ago
Cerebras
Sunnyvale, CA
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Posted 9 hours ago
Dataiku
United States, Remote
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Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams d...
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OpenAI’s Applied AI org is the product development arm of the company, bringing the power of advanced AI models to the world via APIs and user‑interfa...
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Posted 1 day ago
Netomi
Remote - India
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Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, Uni...
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Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, Uni...
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Posted 2 days ago
Tavily
Amsterdam, Netherlands; London, United Kingdom; Remote - Europe; Zurich, Switzerland
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We are seeking a Staff Applied AI Researcher to join a fast-growing team building an agent-native search platform - the web access layer for AI system...
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How it works
Career context
Companies have learned to distinguish engineers who build automation that holds up from those who build impressive demos that break in production. Lead with measurable outcomes: hours saved per week, error rates eliminated, cost reduced. If your automation work has concrete results, those numbers belong in the first line of your profile.
What also sets strong candidates apart is judgment. Knowing when n8n is the right tool and when to write Python. Knowing when an LLM agent adds value and when it adds unnecessary complexity. Companies are tired of over-engineered automation that breaks at the first edge case. If you start with process analysis, build monitoring in from day one, and measure impact. Describe that discipline. It is rarer than it sounds.
Learning the tools? Our guide n8n workflow automation: what n8n costs, five AI workflows you can build, and how it compares with Zapier and Make.
Why RemoteAI
Some roles are posted here by the company, others link to the company's own job page. Closed roles are marked as closed, and there are no recruiter markups.
Roles are filtered to AI work. Each listing shows the company and links to its own job page.
No recruiter in the middle. Your application goes to the company making the decision, here or on its own job page. No markups.
Your profile, browsing and up to 20 applications a day are free. No placement fee, no share of your salary, no exclusive contract.
Jobs posted on RemoteAI show a pay range. Listings from company career pages show it when the company publishes one.
Remote and remote-friendly roles. Some require timezone overlap or a country, and the listing says where you can work from.
Track all your applications, messages, and interviews in one place. No more losing track of where you applied.
Step by step
Pay depends on seniority, location and the company. Many listings on this page show the range the employer published, so compare those directly.
"Automated invoice processing, saving 40 hours/week" beats "built automations in n8n." Quantify every project where you have numbers: companies filter for ROI-oriented candidates.
Low-code (n8n, Make, Zapier) vs. code-first (Python, LangChain) vs. RPA (UiPath) are different profiles. Be clear about which you specialize in and which you can cover.
Mention that your automations include monitoring and fallback handling. It signals professional-grade work and immediately distinguishes you from tutorial-level builders.
Profile guide
Not all profiles get responses. These are the signals that separate candidates who get interviews from those who don't.
Hours saved, error rates reduced, costs eliminated. If you have these numbers, put them first, not buried in a project description.
Automation that breaks silently is worse than no automation. If you build monitoring and alerting into every pipeline, say so explicitly. It is a clear signal of professional-grade work.
LangChain agents, CrewAI, LangGraph: production agentic AI is a distinct specialization. If you have shipped agents that real users depend on, describe them specifically.
Knowing when to use Zapier vs. n8n vs. Python is a skill. Describe a case where you chose a simpler tool over a more complex one and why: it shows engineering maturity.
If you question whether something should be automated before automating it, mention this. Companies are looking for engineers who improve processes, not just automate broken ones.
REST, GraphQL, webhooks, OAuth: virtually all automation connects systems via APIs. If you have built complex multi-system integrations, describe the technical challenges.
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FAQ
Everything you need to know before applying for your first AI automation specialist role.
Create a free profile and browse the AI automation positions on this page. Lead your profile with measurable outcomes from your automation work: hours saved, error rates reduced, processes eliminated. Companies searching for automation specialists filter for ROI-oriented candidates. Specify your tool stack clearly (n8n, Make, Python, LangChain) and whether you specialize in low-code, code-first, or agentic AI automation.
It varies with the specialization: building LLM agents in code is a different job from configuring no-code workflows. It depends on seniority, location and the company, so we do not quote a typical figure. Many listings on this page show the pay range the employer published: compare those directly, and check whether the range is base salary or includes equity.
Lead with your most in-demand tools: n8n, Zapier, Make for low-code; Python, LangChain, and API integration for code-first. For agentic AI: LangGraph, CrewAI, AutoGen, and OpenAI Assistants with tool use. Also highlight error handling and monitoring skills: they differentiate professional-grade automation from tutorial-level work. Quantify outcomes wherever possible: hours saved, processes automated, error rates reduced.
Yes, for normal use. Creating a profile, browsing jobs and applying are free, up to 20 applications a day. Credits are optional: they pay for applications beyond that limit or to put an application at the top of the list. No placement fee when you get hired, no share of your salary, no exclusive contract.
Lead with documented outcomes. The AI automation market is full of people who have built demos. What companies need are engineers who have built automation that runs reliably in production for months. A profile that describes the process automated, the tools used, the error handling built, and the measurable result (hours saved, costs reduced, errors eliminated) stands out immediately from profiles that just list tool names.
It depends on the role. Many companies hire exclusively for no-code and low-code automation (n8n, Make, Zapier) without requiring Python. Others need engineers who can write Python automation, build custom API integrations, or develop LangChain agent systems. Know which type of role you are targeting and match your profile accordingly. Having both (no-code fluency and Python capability) gives you the widest range of opportunities and the ability to choose the right tool for each problem.
Traditional RPA (Robotic Process Automation with UiPath or Automation Anywhere) automates rule-based tasks by mimicking user interface interactions: clicking buttons, copying data between screens. AI automation uses APIs, LLMs, and intelligent agents to handle less structured tasks that require some judgment or natural language understanding. Engineers who can bridge both (understanding when each is appropriate) are valuable in organizations transitioning their automation stack.
Yes. RemoteAI has companies specifically hiring for agentic AI roles: LangGraph for stateful workflows, CrewAI for role-based agent orchestration, AutoGen for multi-agent systems, and custom agent architectures built with LangChain and Python. When applying, describe the agent architecture you built, the tools the agents used, and the reliability challenges you solved. That is what these listings ask about.
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