• You are responsible for the introduction, continuous development, and operation of our AI platforms and AI services • You evaluate new technologies, capabilities, and integrations and translate them into sustainable platform strategies • You ensure that our AI landscape remains secure, scalable, and future-ready • You design governance frameworks, role and permission models, and technical guardrails for the use of AI across the organization • You work closely with Security, Engineering, and other stakeholders to introduce new AI capabilities responsibly • You assess platforms, integrations, and AI services with regard to risk, compliance, and technical feasibility • You take ownership of new AI-related challenges and business requirements • You analyze requirements, develop recommendations, and drive initiatives through to implementation • You support business teams in adopting AI effectively and securely while acting as a trusted technical sparring partner for Business, Security, and Engineering • When needed, you remain hands-on and contribute to integrations, automation initiatives, architecture concepts, and platform solutions

• Diseñar arquitecturas y buenas prácticas agénticas para IA Generativa sobre ecosistema Microsoft Azure. • Definir estrategias de adopción de IA en entornos empresariales. • Interlocución con perfiles de liderazgo y negocio para definir requisitos y estrategia. • Comunicación oral y escrita fluida en inglés.

• Deploy and manage AI platforms supporting enterprise copilots, AI agents, and digital workers. • Implement and maintain Retrieval-Augmented Generation (RAG) infrastructure. • Deploy and manage vector databases and enterprise knowledge systems. • Develop and maintain integrations with RegScale APIs and other enterprise platforms. • Integrate AI services with Microsoft Copilot Studio, Power Platform, Azure AI Services, OpenAI, Anthropic, and related technologies. • Develop automation workflows using Power Automate and API-first architectures. • Design and maintain cloud-native infrastructure supporting AI and automation workloads. • Manage Kubernetes, Docker, CI/CD pipelines, and Infrastructure as Code. • Implement secure deployment pipelines for regulated environments. • Support development of compliance automation workflows for evidence collection, POA&M management, and continuous monitoring. • Monitor AI platform performance, observability, logging, and operational health.

Role Description We are looking for an experienced AI Automation Engineer to design, build, and scale automation solutions and AI-powered workflows across business operations. This is a highly hands-on role where you will work closely with internal stakeholders and external clients to identify process improvement opportunities, implement intelligent automation, and deploy AI agents that drive measurable operational efficiency. You will own projects end-to-end—from workflow discovery and process mapping to implementation, optimization, and ongoing enhancements. The ideal candidate combines operational thinking with expertise in no-code/low-code automation platforms and modern AI tools. Key Responsibilities - Process Analysis & Automation Strategy - Analyze and document existing business workflows across operations, sales, HR, customer support, and other functions. - Identify automation opportunities by evaluating process complexity, frequency, and business impact. - Develop and prioritize automation roadmaps focused on efficiency, scalability, and business value. - Workflow Automation Development - Design, build, test, and maintain automated workflows using platforms such as n8n, Zapier, Make, or similar no-code/low-code tools. - Integrate business systems including CRM platforms, databases, communication tools, and internal applications. - Implement automated notifications, approvals, routing mechanisms, and operational workflows. - System Integration & Data Flow Management - Connect multiple business platforms through APIs, webhooks, and automation frameworks. - Ensure seamless data synchronization and process orchestration across systems. - Develop scalable integrations that improve operational visibility and reduce manual effort. - AI Agent & Intelligence Solutions - Design and deploy AI-powered agents using platforms such as OpenAI, Claude, and other large language model technologies. - Build AI-driven research, analysis, and intelligence workflows. - Develop automated knowledge systems, data enrichment processes, and decision-support tools. - Create AI solutions for both internal teams and customer-facing use cases. - Scoring & Decision Frameworks - Build rule-based workflows and intelligent decision engines. - Implement lead scoring, prioritization models, routing logic, escalation mechanisms, and automated alerts. - Develop business rules that improve operational efficiency and customer engagement. - Client-Facing Solution Delivery - Collaborate directly with clients to understand operational challenges and business objectives. - Design and deliver customized automation and AI solutions tailored to client needs. - Present recommendations, demonstrate solutions, and support successful adoption. - Documentation & Enablement - Create comprehensive process documentation, workflow diagrams, and implementation guides. - Ensure internal teams and clients can effectively manage and utilize delivered solutions. - Establish best practices and reusable frameworks for future automation initiatives. Success Metrics - First 90 Days - Complete workflow analysis and process mapping across key business functions. - Deliver multiple quick-win automation initiatives. - Successfully deploy initial AI-powered automation solutions. - Within 6 Months - Establish a prioritized automation roadmap. - Deliver client-facing AI and automation projects end-to-end. - Create reusable documentation, templates, and operational playbooks. - Within 12 Months - Build a scalable automation and AI ecosystem supporting business growth. - Enable significant productivity improvements through intelligent automation. - Establish repeatable frameworks for automation and AI solution delivery. Qualifications - 3–5 years of hands-on experience building automation workflows using no-code/low-code platforms such as n8n, Zapier, Make, or similar tools. - Experience developing AI agents, AI workflows, or intelligent automation solutions using OpenAI, Claude, or comparable platforms. - Strong understanding of workflow design, process optimization, and operational efficiency. - Experience integrating multiple business systems and applications. - Proven ability to design rule-based workflows, scoring models, and decision automation frameworks. - Strong stakeholder management and communication skills. - Portfolio showcasing automation, AI agent, or workflow implementation projects. Preferred Qualifications - Familiarity with APIs, webhooks, JSON, and basic scripting. - Experience with data enrichment and intelligence platforms. - Background in Revenue Operations (RevOps), Sales Operations (SalesOps), Business Operations, or Process Improvement. - Experience working with CRM systems, marketing automation platforms, and business intelligence tools. - Exposure to AI-powered productivity tools and enterprise automation ecosystems. Key Skills - Must-Have Skills - No-Code Automation - Low-Code Development - AI Agents - Workflow Automation - n8n - Zapier - OpenAI - Claude - Process Mapping - Business Process Automation - Good-to-Have Skills - APIs & Webhooks - Data Enrichment - CRM Integrations - RevOps - SalesOps - Workflow Orchestration - Business Intelligence - Automation Strategy What Makes This Opportunity Unique - Own and shape automation and AI initiatives from strategy through implementation. - Work directly with business stakeholders and clients to solve real operational challenges. - Build impactful AI-driven systems that create measurable business outcomes. - Gain significant ownership, autonomy, and exposure to cutting-edge automation technologies. - Help define and scale the future of AI-powered operations within a fast-growing environment.