AI Technology Strategist & Implementation Lead
14 days ago
Eugene
Job Description Company Overview Modern Amenities is redefining how traditional industries scale by combining AI, data, and platform innovation into one connected ecosystem. We’re more than a single business—we’re building the blueprint for transforming entire markets, starting with the vending and unattended retail space. What we do: • Vendingpreneurs trains entrepreneurs to launch profitable vending routes, creating a ready network of subcontractors to power enterprise contracts., • Modern Amenities partners with REITs, hotel groups, and healthcare facilities to deliver micro-markets and workplace amenities with zero upfront cost—think of us as the “Netflix” of on-site amenities., • VendHub brings the ecosystem together, offering equipment financing, inventory management, and lead generation in one integrated platform. Our impact: From empowering entrepreneurs to servicing national contracts, every solution we create multiplies across multiple business lines. The result: an ecosystem where innovation, efficiency, and opportunity align to unlock billion-dollar potential across industries. Ready to grow with us? Join Modern Amenities at the perfect stage—established enough to scale, but lean enough that your work has immediate impact. Here, ideas become action quickly, and every contribution helps build the future of business. Role Overview Forward-deployed AI specialist responsible for identifying, evaluating, and implementing AI solutions that drive measurable business outcomes. This role combines technology scouting, systems integration, and hands-on implementation to build operational leverage across multiple ventures. You will own the complete lifecycle from technology discovery through deployment, acting as the technical extension of leadership. Full-time Location: Remote/Hybrid (Eugene, OR area preferred) Core Responsibilities • Technology Intelligence & Evaluation (35%), • Monitor AI landscape continuously for emerging tools, platforms, and capabilities, • Maintain pipeline of technologies at different maturity stages (experimental to mainstream), • Run proof-of-concepts and pilot programs to test real-world applicability, • Develop standardized evaluation frameworks (cost, implementation complexity, ROI, integration requirements), • Create business cases for promising technologies with clear migration costs and timelines, • Technical Implementation (35%), • Build and deploy automation systems using Make/Zapier, Clay, Airtable, and API integrations, • Develop data pipelines, lead scoring algorithms, and intelligent routing workflows, • Create voice agents, chatbots, and customer-facing AI solutions, • Audit existing technology stacks across all ventures and document integration points, • Implement webhook integrations and manage technical workflows across platforms, • Strategic Operations (30%), • Map new technologies to specific business use cases and pain points, • Build internal dashboards, reporting systems, and performance tracking tools, • Create implementation roadmaps and process documentation, • Work cross-functionally to identify automation opportunities and efficiency gaps Core Platforms: Framer, Clay, Make/Zapier, Airtable, Notion, Asana AI Tools: Claude API, ChatGPT, various AI automation platforms Integration Skills: Webhooks, APIs, data pipeline creation, system architecture Analytics: Dashboard creation, data visualization, performance tracking Essential Skills & Attributes Technical Competencies • 2+ years building with no-code/low-code automation platforms, • Proven ability to integrate multiple tools into seamless workflows, • Deep understanding of AI capabilities and limitations across different use cases, • Experience auditing technology stacks and identifying integration opportunities, • Connect technology capabilities directly to business outcomes, • Develop ROI-focused business cases with realistic implementation timelines, • Identify bottlenecks and implement systematic solutions, • Balance innovation with practical constraints (budget, time, existing systems), • Extreme ownership mentality: you own outcomes, not tasks, • High agency and bias toward action: you build to test, not theorize, • Comfortable with ambiguity and rapid iteration, • Works at startup pace while maintaining quality standards, • Systematic approach to evaluating new technologies against existing infrastructure, • Can separate signal from noise in rapidly evolving AI landscape, • Creates clear documentation that others can use and maintain, • Conducts thorough pilots with measurable success criteria, • Speed: Average time from technology discovery to implemented solution, • Quality: System reliability, user adoption rates, measurable efficiency gains, • Impact: Documented time/cost savings and revenue contribution from implementations, • Experiments with new AI tools before they are mainstream, • Active on GitHub with proof-of-concepts, • Follows AI communities (Discord, Twitter, LinkedIn) actively, • Builds to see if things work, not just for clear ROI, • Thrives in fast-paced environments owning functions from strategy through execution, • Comfortable building technical solutions and explaining them to non-technical stakeholders, • Active in AI communities (Discord, Twitter, GitHub, LinkedIn), • Multiple side projects using different AI APIs and platforms, • Self-taught on new frameworks and tools, • Comfortable discussing failed projects and lessons learned, • Prototype fast to test hypotheses, • Someone who waits for perfect requirements before starting, • Someone who needs extensive management or direction, • Someone afraid to recommend against hyped technologies when data does not support them, • Someone who builds without measuring outcomes