• Architect compelling solutions utilising all aspects of the Power Platform and the wider Microsoft Ecosystem of Microsoft 365 and Azure. • Manage and complete the discovery, design, build, testing and deployment of solutions utilising the Power Platform and Microsoft Ecosystem. • Seamlessly integrate AI capabilities into business applications, utilising Copilot Studio, Azure AI Foundry and direct API access to different AI providers and models. • Translate editorial and operational needs into scalable, secure, and user-centric system designs. • Leverage large language models and AI-enabled services to design intelligent solutions, and support secure integrations with existing and third-party systems as required. • Lead multiple concurrent AI and automation projects from conception through to production delivery. • Coordinate internal resources, cross-functional teams, and act as the central point of accountability for project success.

• Diseñar, entrenar y optimizar modelos de Machine Learning y Deep Learning para resolver necesidades específicas de negocio • Implementar técnicas de fine-tuning y optimización de modelos generativos y LLMs • Desarrollar soluciones basadas en Retrieval-Augmented Generation (RAG) combinando recuperación de información con generación de contenido • Integrar modelos de IA en aplicaciones mediante APIs RESTful utilizando FastAPI • Diseñar e implementar estrategias de búsqueda semántica utilizando bases de datos vectoriales • Gestionar y optimizar vector databases para consultas de alto rendimiento • Participar en el diseño técnico, revisión de código y evolución de las soluciones de IA

The Opportunity We're looking for a builder who thinks like a product manager and codes like an AI-native developer. Someone who ships revenue-generating systems fast and knows that every internal tool today becomes a client product tomorrow. You'll build AI-powered content systems, RevOps analytics pipelines, and sales intelligence tools. Every system solves a real business problem first—if it works for us, we package it and sell it. That's the AIMS model. If you want to build cool tech demos that don't solve business problems, this isn't for you. If you think in terms of LTV, default to shipping over perfecting, and get excited about turning internal tools into external products, you'll thrive here. If you're curious at heart, genuinely love AI, and light up when you get to build with cutting-edge tools, we should talk. If You Worked Here This Month Built an AI-powered content creation pipeline that produced 47 personalized LinkedIn posts in under 2 hours—then packaged it as "The Content Pod Playbook" deployed across three client accounts Created a RevOps analytics dashboard pulling CRM data via MCP that tracks cost-per-call by lead source across 720 booked calls and flagged a 23% performance drop in one setter before the weekly review Shipped a sales intelligence tool that extracts call transcriptions into a vector database, surfaces the top 5 objections across all client calls, and automatically routes insights to marketing teams—currently processing 150+ calls per week Built a capacity planning dashboard that tracks sales rep availability, identifies coverage gaps 3 days early, and flags which lead sources are falling behind weekly goals What You'll Do Build & Productize: Create AI systems that solve our problems today and become client products tomorrow. Real business value. Ship Fast: Deploy working tools using Claude Code, Cursor, and AI-assisted workflows. Days to production, not weeks to perfection. Own the Infrastructure: Build with MCP servers, RAG pipelines, dashboards, and automated insights that drive business decisions. Bridge Technical & Business: Translate between engineering reality and business needs. Build tools people actually use. Document Everything: Every system becomes a playbook. Every win gets packaged. Every tool gets evaluated for productization. What You Need AI-native development with Claude Code, Cursor, or similar AI-assisted IDEs as your daily driver DevOps fundamentals—Git, CI/CD, containerization, and production discipline MCP server development and connecting AI to real data sources (APIs, databases, CRMs) Vector databases and RAG architecture experience building systems that retrieve and reason over internal data Internal tool building with Streamlit, Next.js, or whatever ships fastest AI security understanding—prompt injection prevention, secrets management, input/output validation Product thinking—you ask "can we sell this?" not just "does it work?" Genuine curiosity—you can name three AI tools you discovered in the last month because you're constantly exploring Bonus: PromptOps experience, orchestration frameworks (LangChain, LangGraph, CrewAI), AI observability tooling (Langfuse, Helicone), experience building tools for marketing/sales operations Who Thrives Here The best people on our team are curious at heart. They genuinely love AI—not as a buzzword, but as a craft they're constantly refining. They're always learning, always experimenting, and naturally excited (not overwhelmed) by how fast this space is moving. They read release notes for fun. They build side projects on weekends. They see every new AI capability as a business opportunity, not just a technical novelty. If that sounds like you, you'll fit right in. What is AIMS? We turn proven RevOps playbooks into AI-powered machines. We're building the operating system for how modern businesses should work. AIMS started from Vendingpreneurs - RevOps systems that generated 1,600+ community members and grew a multi-million dollar portfolio. We asked: "What if we productized these playbooks?" That's exactly what we did. Today, AIMS operates with zero customer acquisition cost. Our client portfolio spans manufacturing, multi-location real estate services, coaching communities, medical services, service-based businesses, and SaaS/retail. What makes us different: - Proven Playbooks: Everything we do has already worked at scale - AI-First: Automation and AI deliver premium results without premium overhead - Built by Operators: We're practitioners, not theorists. We've run these plays ourselves. We're not building another agency. We're building the blueprint for how all agencies should operate in the AI era. Ready to Join? Location: Remote (U.S. preferred for time zone alignment) Employment: Full-Time To Apply: Send your resume and a brief note (3-5 sentences): - The best AI system you've built (with impact metrics) - Why turning internal tools into external products excites you

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous energy engineering problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for energy engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Energy Engineering or related fields, e.g. Electrical Engineering, Power Systems Engineering, Renewable Energy Engineering, Electronics etc. - 3+ years of professional energy engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, EMP, CEM) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.