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Location: Remote
Type: Contract or Full-Time
Company: GreenLight.ai
GreenLight operates at the intersection of global workforce infrastructure, compliance, operations, and AI.
We provide workforce solutions for businesses and talent marketplaces, including EOR, AOR, freelancer management, onboarding, payments, and compliance operations across multiple countries. Our clients include some of the most innovative tech companies in the world and we are growing rapidly.
We are building AI-native systems to automate complex operational workflows, improve decision-making, and scale global workforce operations without scaling headcount.
This role is for someone who wants to build practical AI systems that solve messy real-world problems - not research prototypes.
We are looking for a hands-on Full-Stack AI Engineer who has experience building and shipping AI-powered products, tools, and operational systems in production environments.
This is fundamentally a software engineering role focused on designing, building, and deploying AI-powered workflows, internal tools, assistants, and platform capabilities that improve scalability across GreenLight's operations and products.
You will work directly with leadership, product, operations, and engineering teams to identify opportunities, build solutions quickly, and deploy systems that create meaningful operational leverage.
We value builders who can move from idea to production with minimal oversight and who thrive in fast-moving startup environments.
GreenLight is actively evolving into a more AI-native platform and operational model.
Over the next 6–12 months, AI will become deeply integrated into:
workflow automation
onboarding and operational tooling
support systems
internal knowledge and retrieval systems
operational decision workflows
client and worker experiences
This role will have direct influence over that direction from the beginning.
We are looking for a hands-on Full-Stack AI Engineer who has experience building and shipping AI-powered products, tools, and operational systems in production environments.
This is fundamentally a software engineering role focused on designing, building, and deploying AI-powered workflows, internal tools, assistants, and platform capabilities that improve scalability across GreenLight's operations and products.
You will work directly with leadership, product, operations, and engineering teams to identify opportunities, build solutions quickly, and deploy systems that create meaningful operational leverage.
We value builders who can move from idea to production with minimal oversight and who thrive in fast-moving startup environments.
Examples of projects include:
AI-powered workflow automation
Intelligent onboarding and support systems
Internal AI assistants for operations and compliance teams
AI-driven client and worker support experiences
Knowledge retrieval and operational tooling
Agentic workflows and multi-step reasoning systems
AI integrations across platform operations and customer workflows
We are looking for a hands-on software engineer who can build and ship AI-powered tools, workflow systems, and product integrations in production.
5+ years of software engineering experience, ideally full-stack or backend
Experience shipping production software used by real customers or internal teams
Experience building AI-powered products, internal tools, agents, copilots, or workflow systems
Strong working knowledge of OpenAI and/or Anthropic APIs
Strong experience with APIs, system integrations, and backend workflows
Ability to work independently, move quickly, and make pragmatic technical tradeoffs
Python, Node.js, TypeScript, or similar modern development languages
API integrations, webhooks, workflow orchestration, and internal tooling
RAG, vector databases, embeddings, or knowledge retrieval systems
Cloud infrastructure, deployment, monitoring, and production reliability
Familiarity with tools such as LangChain, LangGraph, n8n, Retool, Zapier, or Make
Background in AI-native companies, venture-backed startups, or high-growth technology businesses
Track record shipping AI-powered products, agents, internal tools, or workflow systems into production
Strong product instincts and ability to translate messy business problems into working software
Comfortable working directly with founders, product leaders, operations teams, and executives
Familiarity with workforce, HR, payroll, compliance, onboarding, support, or payments workflows
Entrepreneurial mindset with high ownership, speed, and bias toward practical outcomes
Within the first 60-90 days, you will have:
Shipped production AI workflows used internally by the team
Built AI-powered tools that materially reduce manual work
Automated operational processes that currently require significant coordination
Delivered platform integrations that improve scalability and efficiency
Created internal AI assistants or workflow systems that improve responsiveness
Established a foundation for GreenLight's AI-powered operational infrastructure
Within 12 months, you will have:
Helped transform GreenLight into a significantly more AI-native business
Delivered measurable operational leverage across multiple departments
Built systems that improve client and worker experiences
Reduced operational overhead through intelligent automation
Influenced the long-term AI and product strategy of the company
We care far more about what you’ve built than formal credentials.
We look for engineers who:
Ship production software
Build practical systems
Move quickly
Make smart tradeoffs
Can turn ideas into working products rapidly
Think like builders and operators
Have a track record of turning ideas into working products
Please include:
GitHub profile
LinkedIn profile
Links to products, projects, or systems you've built
Examples of AI products, agents, workflows, or internal tools you've shipped
Brief explanation of your contributions
OpenAI / Anthropic APIs
n8n / Zapier / Make / LangChain
Python / Node.js
APIs and systems integrations
Vector databases / retrieval systems
Cloud infrastructure and API integrations
We care more about engineering ability and execution than experience with any specific tool.
Large corporate environments
Heavy process and bureaucracy
Long planning cycles before shipping
Pure research environments
Narrowly scoped implementation work
Roles focused primarily on model training or ML research
High ownership and direct impact
Ability to shape core product direction
Direct access to leadership
Opportunity to build meaningful AI systems in a real operational environment
Small, fast-moving team with quick decision-making
Compensation is flexible based on experience, structure, and level of ownership.
We care most about finding the right builder to help shape and execute this next phase of the company.
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