• Design end-to-end solutions that align with enterprise environments and business needs. • Establish and promote best practices, reusable design patterns, and architectural standards. • Create clear and concise documentation, including backend integration specifications, business logic implementation details, and high-level architecture designs. • Identify the APIs needed (Analysis and onboarding, API request/response structures, and DTO classes). • Also designing high level design for the middleware teams to enable them to produce MW services. • Act as a liaison between business stakeholders and development teams to translate business requirements into technical solutions. • Work closely with engineers to support the implementation of designed solutions. • Engage proactively with external teams to ensure alignment and successful project execution. • Tune voice solutions for optimal performance, leveraging best practices in configuration and AI/ML-powered speech recognition systems.

• Design, build, and deploy scalable machine learning and AI systems in production environments. • Collaborate with Product Managers, Data Scientists and Engineers to lead the implementation of models and integrate them into data pipelines and agentic applications. • Lead model performance monitoring, retraining workflows, and continuous improvement. • Lead the implementation of data preprocessing and feature engineering pipelines for ML use cases. • Lead to experimentation and testing of AI models to improve accuracy and performance. • Develop, maintain, and optimize scalable data pipelines for analytics and machine learning workloads. • Ensure data reliability, quality, and performance across data systems. • Implement and maintain data ingestion pipelines from various internal and external sources. • Build and improve internal tools that support data operations and data quality. • Monitor and troubleshoot data pipelines to ensure consistent and timely delivery. • Contribute to improving platform efficiency and scalability. • Participate in code reviews and follow best practices in data and ML engineering. • Document data pipelines, ML workflows, and system architecture. • Contribute to evolving data and AI engineering best practices. • Stay current with emerging tools, frameworks, and trends in AI, ML, and data engineering.

• Define and own Platzi's AI roadmap from infrastructure and tooling to features that directly impact the learner experience • Design, develop, and deploy machine learning models, LLM-powered features, and AI-driven pipelines at production scale • Translate ambiguous product and business needs into concrete technical solutions, working closely with Product, Engineering, and Data teams • Evaluate, prototype, and integrate emerging AI technologies including foundation models, RAG architectures, and agentic frameworks with a bias toward what ships over what's theoretically elegant • Establish engineering practices for model evaluation, monitoring, responsible AI use, and MLOps across the organization • Mentor engineers and grow a team with strong technical judgment and a culture of rapid, deliberate experimentation • Stay ahead of the AI research landscape and identify what's worth applying to real-world problems today not in 18 months • Communicate AI strategy and technical decisions clearly to non-technical stakeholders, including leadership and external partners

Location: EMEA (CET time zone) Beyond our core agency services, we are developing Elevate, a proprietary Marketing Intelligence product featuring a "Universal AI Agent." Our technical vision is to consolidate our diverse internal tools and client-facing agents into a unified, autonomous ecosystem using the Model Context Protocol (MCP). In this role, you will operate as a Senior AI Solutions Engineer. You will have full architectural autonomy to design, build, and deploy complex AI solutions. You will bridge the gap between low-code orchestration and custom backend engineering to solve high-value business problems. Responsibilities Product Engineering (Elevate & Core Infrastructure) - Architect and build the Universal Agent: Design the central orchestration layer for our "Elevate" platform, allowing the AI to autonomously perform complex actions across integrated marketing tools. - Implement MCP Strategy: Lead the adoption of the Model Context Protocol (MCP) to standardize how our agents connect to external APIs, databases, and third-party platforms. Client & Agency Automation - Bespoke Agent Development: Prototype and deploy specialized AI agents or automation workflows for our internal process automation and B2B clients (e.g. Automated File handling, Data Analysis Pipelines, Automated Reporting). Technical Implementation - Advanced Integrations: Build custom connectors for complex APIs, handling authentication and data transformation programmatically. - Custom Tooling: Extend the capabilities of standard automation platforms by writing custom nodes, scripts, and microservices in TypeScript or Python. - Reliability Engineering: Ensure all workflows are production-grade, implementing comprehensive error handling, logging, and rate-limit management strategies. - Engineering Background: 5+ years of experience in software development (Backend focus) with a strong portfolio of AI/Automation projects. - Coding Proficiency: Strong production skills in TypeScript (Node.js) or Python. You must be comfortable writing code when low-code tools reach their functional limits. - API Architecture: Experience working with REST, GraphQL, and Webhooks. Ability to reverse-engineer private APIs when necessary. - LLM Architecture: Deep understanding of Large Language Models, including Prompt Engineering (OpenAI, Anthropic), Function Calling (Tool Use), Embeddings and RAG. - Automation Workflows Expertise: Experience with workflow automation software and workflows like N8N, Zapier, Make or Langchain - Database Knowledge: Proficiency with SQL and Vector Stores. Why Join Us? - Architectural Freedom: You define the technical approach. We focus on the outcome, giving you the autonomy to choose the right tools for the job. - Product Impact: You are not just building temporary scripts; you are engineering the core intelligence logic for the "Elevate" product. - Advanced Tech: We are early adopters of standards like MCP, offering you the chance to work with the latest developments in Agentic AI. Conditions - USD compensation that values your expertise.‍ - Work from anywhere: Fully remote to suit your lifestyle.‍ - 31 days of paid time off: 21 days of annual leave + 10 days of sick leave, because your health and work-life balance matter.‍ - Growth-focused environment: Access to learning resources and clear pathways for growth.‍ - Fun team events: Virtual cooking classes, yoga sessions, team quizzes and more. - ‍A culture of trust: We cut the red tape — results over rules always. Open talk, ownership, and getting things done together. AI Digital does not discriminate on the basis of race, color, religion, gender identity or expression, national origin, age, military service eligibility, veteran status, sexual orientation, marital status, disability, or any other protected class in terms of employment. We support workplace diversity and believe strongly that it contributes to a broader collective perspective that consistently leads to better products and a better company. We are working hard to increase the diversity of our team.