Role Description Estamos en búsqueda de un/a AI Full Stack Engineer – Document Intelligence. Buscamos un perfil técnico con experiencia en desarrollo e industrialización de soluciones de Inteligencia Artificial para procesamiento documental, capaz de conectar ciencia de datos, ingeniería de software y operaciones para construir aplicaciones de IA escalables y listas para producción. La posición formará parte de un equipo especializado en IA Generativa y Agentic AI, desarrollando capacidades avanzadas de extracción, clasificación, análisis y explotación de documentos dentro de un entorno bancario empresarial. - Diseñar, desarrollar y mantener aplicaciones de IA enfocadas en procesamiento documental e inteligencia documental. - Implementar soluciones basadas en NLP, OCR, embeddings, clasificación de texto, similitud semántica y extracción de información. - Desarrollar y mantener APIs asociadas a capacidades de IA y Machine Learning. - Desplegar, monitorizar y mantener aplicaciones productivas en entornos Kubernetes. - Participar en la construcción y evolución de pipelines CI/CD. - Aplicar buenas prácticas de testing, calidad de código y seguridad. - Colaborar estrechamente con Data Scientists, Product Owners, CTOs y equipos de ingeniería. - Contribuir a la industrialización y escalabilidad de soluciones de IA Generativa y Agentic AI. Qualifications - Alrededor de 4 años de experiencia desarrollando y manteniendo aplicaciones productivas con componentes de IA. - Experiencia sólida en Python y SQL. - Experiencia desplegando aplicaciones en Kubernetes. - Desarrollo de APIs para servicios de IA y Machine Learning. - Conocimiento de Git y procesos CI/CD. - Experiencia con herramientas de calidad, testing y seguridad como Pytest, Sonar, Fortify o similares. - Conocimientos prácticos de NLP: tokenización, embeddings, clasificación de texto y similitud semántica. - Experiencia con IA Generativa, LLMOps y arquitecturas basadas en agentes. - Experiencia con frameworks como LangGraph, LangChain, CrewAI, MCP o similares. - Experiencia en aprendizaje supervisado y no supervisado aplicado a casos reales. - Experiencia práctica en OCR y procesamiento documental. Requirements - Muy valorable: - Experiencia diseñando e implementando procesos ETL con Python y Spark. - Experiencia con Airflow, Control-M u otras herramientas de orquestación. - Experiencia en AWS (especialmente Step Functions) y/o Azure Functions. - Conocimientos de Infraestructura como Código (Terraform). - Experiencia con MLflow o Kubeflow. - Experiencia en Databricks o Cloudera. - Conocimiento de Kafka o tecnologías de streaming. - Experiencia con Kibana, Dynatrace o herramientas de observabilidad. - Conocimiento de ElasticSearch, MongoDB, PostgreSQL, Starburst o S3. - Experiencia en soluciones RAG y chatbots basados en IA Generativa. - Conocimientos de JavaScript, TypeScript o C++. - Experiencia con optimización matemática y motores como Gurobi, CPLEX, CBC o Pyomo. - Conocimiento de herramientas BI como Power BI. Benefits - Contrato indefinido con salario competitivo. - Modalidad 100% remota. - Plan de carrera personalizado y formación continua. - Participación en proyectos innovadores de IA Generativa y Agentic AI. - Entorno internacional y colaboración con equipos globales. - Flexibilidad horaria y enfoque en la conciliación. - Beneficios sociales adaptados a tus necesidades.

• Architect and own the MCP server ecosystem across Bio-Tech / Healthcare enterprise application portfolio • Build production-grade MCP servers in TypeScript and Python with OAuth 2.0, RBAC, and audit logging • Define tool schemas, versioning standards, and multi-agent orchestration patterns • Integrate MCP servers with SAP, Salesforce, D365, Smartsheet, Jira, Microsoft Graph API, and other business applications as per business need • Design the tool invocation and RBAC model for AI virtual employees and internal copilot personas • Align architecture with Bio-Tech / Healthcare AI Security Reference Architecture and EU AI Act compliance (Aug 2026) • Maintain an MCP server registry and contribute to internal Claude AI Launchpad enablement • Mentor AI & Automation Developers on MCP patterns and agentic integration best practices

Role Description This position will work on a small, agile team developing highly scalable, cloud-based applications that allow our customers to leverage our video, data, and machine learning platforms. Our engineers are actively delivering high-quality code while continuously improving the development practice, product, and team. The ideal candidate brings a strong background in backend data pipelines, serverless architecture, and AI/ML system integration. - Collaborative Development: Actively participate in a collaborative development team with the opportunity to influence product direction and mentor team members. - Serverless & Cloud Architecture: Design, develop, and deploy REST-based services and data pipelines using Serverless Technologies like AWS, Serverless Framework, and NodeJS. - UI & Dashboard Enhancement: Enhance and optimize responsive web application dashboards using React, building interactive data visualizations and modern UI components. - Data Engineering & AI Integration: Build robust ETL pipelines and integrate AI-generated insights, risk models, and generative AI/LLM components into customer-facing applications. - Automated Testing & QA: Verify the soundness and performance of features by developing end-to-end automated testing frameworks (using Cypress, Pytest, or similar tools) as part of initial feature development. - Reliability & DevOps: Maintain and optimize CI/CD pipelines using Docker and Kubernetes to ensure solutions are monitored, robust, and deployed with high uptime. - Video Platform Engineering: Work on core video-processing pipelines, leveraging computer vision tools to handle automated video editing, frame selection, and motion detection. Qualifications - 4+ years of experience developing commercial software, data pipelines, or AI/ML applications. - 2+ years of experience working with modern web application frameworks, with a distinct focus on React and its ecosystem (e.g., state management, form validation, and responsive design libraries). - 3+ years working in a cloud-hosted environment (AWS or GCP), including strong hands-on experience with serverless computing and containerization (Docker, Kubernetes). - Excellent JavaScript development skills alongside strong Python proficiency for data processing, scripting, and backend development. - Strong relational SQL skills (PostgreSQL, Redshift) with the ability to design data schemas, manage data warehouses, and optimize complex queries. - Strong grasp of Agile principles, comfort with changing requirements, and experience troubleshooting legacy systems using debugging tools and tracking systems (e.g., JIRA). - Excellent written and verbal communication skills, with a proven ability to collaborate across cross-functional teams and international clients. - Be a self-starter who enjoys tackling new problems, conducting user-testing, and delivering innovative end-to-end solutions. Requirements - Bachelors degree with 1+ years of experience developing software applications OR Masters degree with 0+ years of experience developing software applications. Benefits - Incentive Bonus Plans - Medical, Dental, Vision benefits - 401K with Company Match - 10 Paid Holidays - Generous Paid Time Off Packages - Employee Stock Purchase Plan - Paid Parental & Family Leave - and more!

• Set the technical direction for AYBI's AI and GenAI work, the architecture, the build-vs-buy calls, and the honest judgment of when AI is the wrong tool. • Build and ship AI into our products and client solutions, LLM applications, RAG over messy real-world data, agents and tool-calling, and make them production-grade, not demo-grade. • Own reliability: evals as the unit tests of our AI (eval suites in CI, golden datasets), observability and tracing on every call, and guardrails against hallucination and prompt injection. • Keep AI affordable: track cost and latency per task, and use caching, routing, and the right model for the job rather than the biggest one. • Lead the productization push the team is starting, turn one-off work into repeatable, observable, dependable products, with the testing and monitoring to match. • Lift the engineers around you, through craft, clear direction, and the occasional workshop, and help the whole team adopt AI well. • You lead through your roles and accountabilities, not a reporting line; we self-organise. • Translate AI capability into real client value and push back on anything that's AI for AI's sake. • Stay close to the frontier: read what's new, test what's promising, bring back what's worth it.