AI Engineer / AI Automation Specialist

Pavago

United States

Remote

USD 120,000 - 190,000

Full time

3 days ago

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Job summary

Pavago is hiring an AI Engineer / AI Automation Specialist to build AI-powered applications, intelligent agents, and business automations. This hands-on role covers idea-to-implementation across generative AI, API integrations, and workflow automation.

You will develop agentic workflows using LLMs, tools, and business logic, with strong emphasis on reliability, testing, and maintainable code. Remote work aligns with US business hours.

Qualifications

Hands-on software development with AI and automation
Experience building AI-powered apps, workflows, or automations
Experience integrating APIs and third‑party platforms
Proficiency in Python and/or JavaScript/TypeScript
Familiarity with AI coding tools and agentic workflows
Strong problem-solving and independent project execution

Responsibilities

Design and build AI-powered applications and workflows
Develop AI agents that can execute structured tasks and business processes
Create agentic workflows using LLMs, tools, APIs, and business logic
Turn manual processes into scalable AI-assisted systems
Improve existing AI applications as requirements evolve

Skills

Python

JavaScript/TypeScript

LLMs

AI workflows

APIs

Agentic development

Troubleshooting

English communication

Tools

Make

Zapier

n8n

Job description

AI Engineer / AI Automation Specialist – LLMs, AI Agents & Workflow Automation | Remote

Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours

About the Role

At Pavago, one of our clients is hiring an AI Engineer / AI Automation Specialist to build AI-powered applications, intelligent agents, integrations, and business automations.

This is a hands‑on technical role for someone who can take an AI or automation use case from idea to working implementation. You’ll combine software development, LLMs, APIs, automation platforms, and agentic workflows to build systems that reduce manual work and improve business efficiency.

You’ll work across generative AI, AI agents, API integrations, workflow automation, prompt engineering, and internal tooling, while continuously evaluating emerging AI technologies.

What You’ll Own

AI Applications & Agent Development

Design and build AI-powered applications and workflows
Develop AI agents that can execute structured tasks and business processes
Build agentic workflows using LLMs, tools, APIs, and business logic
Turn manual processes into scalable AI‑assisted systems
Improve existing AI applications as business requirements evolve

LLM & Generative AI Integration

Integrate LLMs with internal systems and third‑party platforms
Build structured workflows around generative AI models
Develop and refine prompts, tools, and reusable AI components
Implement reliable structured outputs and workflow logic
Evaluate AI responses for quality, consistency, and reliability

Automation & Business Workflows

Build automated workflows that reduce repetitive manual work
Connect applications and business systems using APIs and automation platforms
Develop workflows using tools such as Make, Zapier, n8n, or similar platforms
Troubleshoot failed or unreliable automations
Continuously improve workflow efficiency and scalability

APIs & Integrations

Build and maintain API integrations between AI systems and external platforms
Work with webhooks and third‑party services
Manage data flows between applications and automation workflowsTroubleshoot integration issues and improve system reliability

Development & Internal Tools

Build internal tools that improve team productivity and operational efficiency
Develop technical solutions using Python and/or JavaScript/TypeScript
Write clean, maintainable code for AI and automation systems
Use modern AI coding tools to accelerate development and debugging
Support deployment and ongoing maintenance of AI‑powered solutions

AI Quality, Testing & Reliability

Evaluate AI output quality and reliability
Test prompts, workflows, agents, and integrations
Identify edge cases and failure points
Improve AI systems based on real‑world performance
Build appropriate safeguards and validation into automated workflows

Research & Experimentation

Research and test emerging AI technologies
Evaluate new LLMs, agent frameworks, AI coding tools, and automation platforms
Identify practical opportunities to apply new technologies
Recommend improvements based on testing and business impact

Documentation & Process Development

Document AI systems, workflows, integrations, and processes
Create clear technical documentation for ongoing maintenance
Maintain organized records of automation logic and system dependencies
Build repeatable processes that allow successful solutions to scale

Requirements

Professional experience in software development, automation, AI, or a related technical role
Hands‑on experience working with LLMs and generative AI
Experience building AI‑powered applications, workflows, or automations
Experience integrating APIs and third‑party platforms
Programming experience, preferably with Python and/or JavaScript/TypeScript
Familiarity with AI coding tools and agentic development workflows
Understanding of prompt development and structured AI workflows
Strong troubleshooting and problem‑solving skills
Ability to independently take projects from concept through implementation
Strong written and spoken English
Comfortable working independently in a remote environment

Nice to Have

Experience with Make, Zapier, n8n, or similar automation platforms
Experience building AI agents or multi‑step agentic workflows
Familiarity with webhooks and event‑driven integrations
Experience developing internal business tools
Experience working with structured LLM outputs and tool/function calling
Familiarity with cloud deployment and modern development workflows
Experience evaluating and monitoring AI system performance

Tools & Technologies

What Makes You a Strong Fit

You’ll likely thrive in this role if you:

Build with AI rather than simply use AI for basic productivity
Enjoy turning manual workflows into automated systems
Can move from an idea to a functional technical solution independently
Understand both software development and business automation
Experiment with new AI tools and technologies regularly
Think critically about AI reliability rather than assuming outputs are correct
Are comfortable troubleshooting across APIs, code, and automation platforms
Prioritize practical business impact over experimentation for its own sake

What a Typical Day Looks Like

Your day may include building an AI agent, connecting an LLM to a business platform through an API, developing an automation in n8n or Make, troubleshooting an existing workflow, or creating an internal tool that eliminates repetitive work.

You may also test prompts and agent behavior, evaluate AI output quality, document systems, and research emerging AI technologies that could improve existing workflows.

In short: you turn AI capabilities into practical, reliable systems that automate work and improve business operations.

Key Metrics for Success