AI Automation & Agent Builder - Aspire

Aspire Software is looking for an AI Automation & Agent Builder to join our team in Lebanon.

Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.

About theAI-Driven Automation

The AI Automation & Agent Builder Engineer is an AI-first builder responsible for designing, building, and shipping intelligent agents and automated workflows that replace manual work and generate measurable business value. This role is not a research or experimentation role. AI Automation Engineers are embedded directly inside portfolio company teams, understanding real operations, and deploying agents that handle real work — customer service, sales outreach, onboarding, document processing, and more.

Some of what you build will replace manual workflows within Aspire’s portfolio companies. Some of it will become new revenue-generating products sold to their customer bases. Either way, it ships to real users and is measured by real impact. This role is foundational in AI-native organizations and is often the highest-ROI AI position in the company.

Core Responsibilities

• Build Internal AI Agent Teams
• Design and deploy AI agents that handle operational work across portfolio companies — including customer support (Tier 1 & 2), SDR and sales outreach, onboarding automation, content workflows, and engineering maintenance
• Automate core business processes: CRM updates, document processing, reporting, and analytics pipelines
• Work directly with portfolio company operators to identify the highest-value automation opportunities
• Measure impact in hours of labor replaced, team output increased, or cost savings generated

Build External AI Products

• Develop new AI-powered products such as vertical voice agents, AI copilots, workflow automation tools, and AI documentation systems tailored to vertical markets
• Own the product from prototype through launch, including reaching first paying customers
• Integrate AI capabilities with existing systems: CRM, ERP, internal tools, SaaS platforms, and third-party APIs
• Build agentic workflows including multi-agent coordination, decision engines, and tool-using AI agents

Ship and Iterate

• Move fast from idea to MVP to production — bias toward working software over documentation
• Run beta tests with real users, gather feedback, and improve continuously
• Optimize AI agent performance: latency, cost, accuracy, and human intervention rate
• Ensure production reliability through monitoring, evaluation, and model lifecycle management
• Collaborate cross-functionally with product, engineering, and go-to-market teams

What This Role Is Not

• Not a research or proof-of-concept role — everything you build ships to real users
• Not a traditional backend or systems engineering role focused on ticket execution
• Not bound by story points, sprint rituals, or rigid SDLC stages
• Not limited to internal tooling — what you build may become a product customers pay for

Requirements:
Core Capabilities

• Proven track record of building products, tools, automations, or side projects that went live and created real impact
• Strong working knowledge of AI and machine learning tools, large language models (LLMs), and agent frameworks
• Ability to go from zero to functional prototype quickly
• Comfort with ambiguity — you will often be defining the problem as much as the solution
• Bias toward action over planning

Technical Skills

• Hands-on experience with LLM integrations, RAG architecture, and prompt engineering
• Proficiency with workflow orchestration and automation platforms (e.g. n8n, Zapier, Make, LangChain, CrewAI)
• Ability to build and maintain API integrations across CRM, ERP, and SaaS systems
• Understanding of vector databases, embedding pipelines, and model hosting
• Strong debugging and problem-solving skills across full AI system stacks

Mindset & Approach

• Outcome-oriented: you measure success in labor hours saved, revenue generated, and adoption rate — not tickets closed
• Strong operational intuition — ability to understand a business workflow and identify where AI creates the most leverage
• Comfortable working directly with business operators, not just engineering teams
• Ability to reason about AI system limitations, failure modes, and appropriate human-in-the-loop design

Key Performance Indicators (KPIs)

Automation Impact

• Number of business processes automated
• Hours of manual labor saved per month
• Reduction in manual task volume across portfolio companies

Agent Performance

• Agent task success rate
• Agent accuracy and hallucination rate
• Human intervention rate (lower = better)

Efficiency & Business Value

• Cost savings generated through automation
• Response time improvements across automated workflows
• Operational throughput increase

Delivery & Adoption

• Number of AI agents and automations shipped per quarter
• Time from idea to production deployment
• Number of teams actively using AI agents built by this role
• Internal workflow adoption rate