Acerca del Grupo QuintoAndar
Somos el Grupo QuintoAndar, el mayor ecosistema inmobiliario de América Latina. Guiados por un propósito compartido de ayudar a las personas a amar el lugar donde viven, contamos con un portafolio diversificado de marcas y soluciones en diferentes países de América Latina y también con un Hub de Tecnología en Portugal. Desarrollamos tecnologías e innovación para transformar e impulsar la experiencia de vivienda en su totalidad.

Juntas, nuestras marcas líderes ofrecen soluciones que cubren todas las etapas del proceso de viviendar: Inmuebles24 (México), Zonaprop (Argentina), Adondevivir y Urbania (Perú), Plusvalía (Ecuador), ImovelWeb y QuintoAndar (Brasil).

Con el apoyo de un equipo de inversionistas y consultores de clase mundial, como Kaszek, Qualcomm, General Atlantic y SoftBank, QuintoAndar Group está actualmente valorado en más de 5.100 millones de dólares y sigue creciendo año tras año.

Aquí trabajarás con los mejores profesionales del mercado, en un entorno que respira innovación, colaboración y alto rendimiento. Para conocer más sobre nuestra historia, visita https://grupoquintoandar.com/es/.

Ubicación y Modelo de Trabajo Híbrido 
Nuestro equipo de Software Engineer trabaja bajo el modelo “híbrido”, siendo necesario estar presencialmente en la oficina, ubicada en Buenos Aires, 1 vez por semana al menos.

Etapas  del Proceso Selectivo:

Las etapas de nuestros procesos de selección tienen como objetivo evaluar tus experiencias y brindarte la oportunidad de conocer a nuestros equipos y oportunidades de carrera, y están estructuradas en los siguientes pasos:

• People Interview
• Tech Screening 
• Tech Interview 1
• Tech Interview 2

Acerca del puesto 

En nuestro equipo de Data Science, tendrás la oportunidad de trabajar como parte de nuestros product squads, desarrollando funcionalidades que enriquecen nuestro producto y brindan la experiencia de primer nivel por la que somos reconocidos. Trabajarás junto a profesionales brillantes con distintas especialidades: Product Managers, Designers, UX Writers, Data Scientists, Machine Learning Engineers, Software Engineers, entre otros. Prepárate para el trabajo de tu vida: desafíos complejos, altas expectativas, mentes brillantes trabajando juntas, conversaciones significativas y una productividad extraordinaria.

Algunos de los problemas específicos en los que trabajamos en el equipo de Data Science incluyen sistemas de búsqueda y recomendación; mejora de la experiencia del cliente utilizando machine learning (como el enrutamiento automático de tickets); modelos de pricing, liquidez y crédito; y la construcción de una plataforma que nos permita desarrollar y desplegar todas estas soluciones.

Nota: Esta es una posición senior. Esperamos que tengas al menos 3+ años de experiencia aplicando Data Science y creando modelos de machine learning. Si tienes las habilidades pero estás comenzando tu carrera en Data Science, te recomendamos postularte a la posición de Data Scientist.

Responsabilidades

• Arquitectar, desarrollar y desplegar sistemas de machine learning en producción. Los principales casos de uso están relacionados con chatbots y sistemas de búsqueda.

• Diseñar y ejecutar experimentos.

• Analizar una amplia variedad de datos (estructurados y no estructurados, observacionales y experimentales) para mejorar los modelos actuales o crear nuevos.

• Aplicar el método científico para desarrollar aplicaciones impulsadas por LLMs, incluyendo probar diferentes prompts, explorar y comprender las capacidades de los LLMs, evaluar agentes y prompts, analizar guardrails de aplicaciones de IA y construir PoCs para validar la viabilidad de IA generativa en funcionalidades de producto.

• Participar activamente en discusiones y decisiones relacionadas con todo el chapter de Data Science (Guilds, Design Reviews, Demos, etc.).

Lo que buscamos

• Personas que quieran aprender y generar impacto real a través de Data Science.

• Conocimiento experto en conceptos de machine learning: regresión y clasificación, clustering, redes neuronales, selección de features, validación cruzada, curse of dimensionality, bias-variance tradeoff, explicabilidad de modelos, entre otros.

• Buena comprensión de los desafíos de ingeniería para desplegar sistemas de machine learning en producción.

• Dominio de Python.

• Conocimientos o experiencia con Deep Learning.

• Experiencia brindando asesoramiento técnico a otros data scientists (liderazgo técnico).

• Excelentes habilidades de comunicación técnica escrita y verbal. Buscamos a alguien apasionado por Data Science y Machine Learning, dispuesto a compartir su conocimiento con los demás miembros del Data Science Chapter.

• Buen nivel de inglés (oral y escrito) es obligatorio.

Te destacarás si

• Tienes un MSc. (o licenciatura + experiencia sólida) en machine learning, data science, information retrieval, ranking systems, recommender systems, natural language processing u otros campos relevantes.

• Tienes experiencia con IA generativa aplicada: agentes de IA, prompt engineering, fine-tuning de LLMs (LoRA, QLoRA, PEFT), LLM routing, monitoreo de LLMs y LLM guardrails.

• Tienes experiencia trabajando en startups de rápido crecimiento.

Importante:

• ¡Nuestro proceso de selección comienza con el registro! Si realmente deseas formar parte de nuestro equipo, asegúrate de completar  esta primera etapa. Revisamos cada postulación con atención y siempre damos una respuesta, aunque la persona no siga en el proceso. 
• Toda la comunicación se realiza por correo electrónico, así que estate atento a nuestros mensajes y libera el dominio @quintoandar.com.br para que nuestros correos no terminen en la carpeta de spam.

Beneficios

• Plan médico
• Wellhub
• Licencia parental extendida
• Reintegro de Guardería
• Gastos de teletrabajo (monto mensual)
• Descuentos en servicios del día a día
• Día libre por cumpleaños, Día del Padre y Día de la Madre

Diversidad e Inclusión en Grupo QuintoAndar

Durante la inscripción, verás algunas preguntas sobre diversidad. Estas son confidenciales y tienen como objetivo apoyar nuestras acciones de diversidad e inclusión. En vacantes afirmativas, la información podrá ser utilizada para verificar el alineamiento con el público objetivo de la oportunidad y, en estos casos, podría tener carácter eliminatorio. Para vacantes no afirmativas, esta información no afecta tu postulación y se utiliza únicamente para ayudarnos a mejorar continuamente nuestras prácticas e iniciativas de inclusión a lo largo de tu trayectoria con nosotros.

Privacidad y Protección de Datos

El Grupo QuintoAndar actúa de conformidad con las leyes de privacidad y protección de datos, y garante la seguridad de sus datos personales. Para saber más, consulte nuestro Aviso de Privacidad para Personas Candidatas. Si tiene dudas o desea ejercer sus derechos como titular de los datos, póngase en contacto con nosotros a través de nuestro Canal de Atención.

#LI-FS4

Why You'll Love This Role: 

We're looking for an experienced ML Ops Engineer to join the ML/AI team at Newsela. This team works on projects ranging from classical Machine Learning to AI / Generative pipelines.  This is a hands-on role. You'll work closely with ML/AI, data and site reliability engineers to take models from prototype to production, build robust data pipelines, and keep our services running smoothly as we continue to scale.

What You'll Be Doing:

• Design and maintain CI/CD pipelines for ML model training, packaging, and deployment across our microservices.
• Manage containerized services on AWS ECS, optimizing for cost, latency, and availability.
• Automate infrastructure provisioning and service configuration with Terraform.
• Work to maintain and scale services that make use of third party LLM providers.
• Build and improve data pipelines that feed models from BigQuery, S3, and DynamoDB into training and inference workflows.
• Instrument services with observability tooling (Datadog, OpenTelemetry, Langfuse) and establish SLOs for model-serving endpoints.
• Collaborate with ML engineers to productionize new models using BentoML, FastAPI, and container-based serving.

About You:

• 2-3 years in ML Ops supporting ML/AI features, systems and workflows with 3-4 years prior experience in DevOps, CloudOps or SRE.
• Strong proficiency in Python.
• Hands-on experience with Docker containerization and container orchestration.
• Solid understanding of CI/CD for ML workflows in an enterprise production environment.
• Experience with Infrastructure as Code, preferably Terraform.
• Familiarity with cloud platforms — specifically AWS (ECS, ECR, S3, DynamoDB, CloudWatch) and GCP (BigQuery, Vertex AI).
• Experience with LLM integration and observability (OpenAI API, Google GenAI, Langfuse tracing).
• Experience building and maintaining data pipelines for ML training and feature engineering
• Familiarity with ML modeling workflows — training, evaluation, experiment tracking (e.g. MLFlow, Weights & Biases), and model versioning
• Experience monitoring and flagging model drift over time.
• Exposure to NLP/NLU models and frameworks such as Hugging Face Transformers, spaCy, or sentence-transformers
• Knowledge of vector databases (LanceDB, FAISS) and embedding-based retrieval systems
• Experience with scaling and maintaining deep learning frameworks (TensorFlow, PyTorch) in production settings
• Familiarity with classical ML libraries (scikit-learn, XGBoost, LightGBM) and model explainability tools (SHAP)
• Working knowledge of ML serving frameworks such as BentoML or similar.
• Comfort working with FastAPI or similar async Python web frameworks.

Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits

About Newsela:

Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner.

#LI-Remote

Santex es una empresa global con sede en EE. UU., fundada en 1999, con 26 años de experiencia en la industria del software. Con oficinas centrales en California y en Córdoba, Argentina, su red de talento se extiende por más de 18 países gracias a su cultura flexible y de trabajo remoto. Santex se especializa en el desarrollo de software empresarial a medida, operando a través de Hubs que abarcan comercio electrónico, BIM, movilidad, distribución de contenido, integración, desarrollo web y móvil, computación en la nube, inteligencia artificial (IA), ciencia de datos, consultoría de TI y servicios. La empresa está comprometida con generar un impacto positivo en tres dimensiones: económica, social y ambiental.

Job Description: AI Specialist

Purpose: Diseñar, entrenar y mantener soluciones de inteligencia artificial, incluyendo modelos predictivos, asistentes conversacionales y productos core (como SAM Core), garantizando la viabilidad técnica de las pruebas de concepto (POC) y aportando visión técnica para estimaciones y diseño de soluciones.

Critical Tasks

• Diseño y entrenamiento de modelos AI
• Crear y ajustar modelos predictivos adaptados a las necesidades de cada prueba de concepto.
• Mantenimiento de plataformas AI
• Operar y mantener SAM, asegurando estabilidad, rendimiento y actualización continua.
• Soporte técnico para POC
• Colaborar en la construcción técnica de las pruebas, mostrando capacidades, estimando tiempos y definiendo equipos necesarios.
• Consultoría técnica interna
• Asesorar sobre tecnologías aplicables, mejores prácticas y arquitecturas para futuros proyectos.

Essential Functions

• Desarrollar soluciones backend AI
• Implementar, ajustar y mantener modelos y arquitecturas para cada proyecto.
• Estimar esfuerzos técnicos
• Analizar requisitos, calcular tiempos y recursos necesarios para garantizar la viabilidad técnica.
• Asegurar la calidad técnica
• Velar por la robustez, seguridad y rendimiento de los productos y plataformas AI.
• Colaborar con el Product Manager
• Trabajar en conjunto para alinear visión técnica y objetivos de negocio.

Professional experience:

• Experiencia desarrollando soluciones backend AI.
• Experiencia en diseño y entrenamiento de modelos predictivos.
• Plus: mantenimiento de plataformas conversacionales.

Leadership Competences:

• Visión Estratégica: Comunicar de manera clara y efectiva ideas técnicas y complejas tanto a colegas técnicos como a stakeholders no técnicos. Debe demostrar habilidades de escucha activa para poder identificar necesidades y preocupaciones
• Comunicación Efectiva: Habilidad para comunicar claramente la visión, estrategia y progreso del producto a todos los niveles de la organización.
• Trabajo en equipo: trabajar efectivamente con diversos equipos y facilitar la coordinación entre departamento
• Coraje: Promover y gestionar tensiones en pos de la disrupción. Ver los riesgos como una oportunidad.

Formación Académica:

- Profesional en Ingeniería en Sistemas, Ciencias de la Computación, Matemática, o afines.
- Formación complementaria: Cursos en machine learning, NLP, deep learning.

Languages: Español. - Inglés

Locación: CABA o Córdoba

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated Marketing Analyst- Comms who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

The Marketing Analyst - Comms, will sit at the intersection of data, CRM strategy, and AI-driven efficiency. We’re looking for an execution-oriented person who owns their work from end-to-end. You'll dive into the details of how our campaigns operate across email, push, SMS, and in-app channels, spot friction and inefficiency, and design smarter ways forward. You'll spend most of your time inside Braze, Sezzle's primary consumer-focused CRM and marketing automation platform, building and analyzing campaigns across email, push, SMS, and in-app channels. You'll dig into performance data to identify what's working, surface gaps in our consumer journeys, and develop new comms to fill them. You'll also look for every opportunity to apply AI tools to make the team's output faster, sharper, and more scalable.
This isn't a role where you wait for assignments. We want someone who can look at a set of data, identify the opportunity, and start building toward it then communicate what  they found and why it matters to the team around them.

What You'll Do:

• CRM Campaign Execution & Analysis

  • Build, launch, and iterate on campaigns and canvases in Braze across email, push, SMS, and in-app channels.

  • Audit existing consumer journeys to identify engagement gaps, drop-off points, and missed messaging opportunities.

  • Develop segmentation strategies and personalized comms that improve activation, engagement, and retention.

  • Support A/B test design, execution, and readout — translating results into clear, actionable recommendations.

  • Maintain performance dashboards and reporting frameworks that make campaign data interpretable for the broader marketing team.

  • Track KPIs including DAU, ARPDAU, LTV per user, open rates, click rates, and conversion, and surface insights tied to those metrics.

  • Effectively manage our marketing CRM tool to drive new and innovative use cases that can be shared across the team

  • Write SQL queries to investigate issues and campaign results using internal data

  AI, Automation & Process Optimization

  • Identify opportunities to apply AI tools and automation across marketing workflows from copy generation to campaign QA to performance analysis.

  • Build and iterate on tools, templates, and agents that reduce manual effort and improve output consistency.

  • Stay current on emerging AI/automation capabilities and bring concrete recommendations for how they can be applied within Sezzle's marketing stack.

  Cross-Functional Collaboration

  • Partner with marketing, product, data, and engineering teams to align on tooling decisions and ensure smooth implementation.

  • Serve as a connector between technical teams and marketing stakeholders, translating requirements in both directions.

  • Facilitate adoption of new tools and workflows by developing documentation, training materials, and hands-on support for team members.

  • Identify and flag integration risks early; bring concrete mitigation recommendations.

What We Look for:

• Skills & Competencies

  • Hands-on experience building or implementing AI tools, agents, and automation in a professional setting.

  • Strong analytical skills, comfortable working with data, running queries, and presenting findings with context.

  • Experience in consumer marketing operations, CRM platforms (Braze or similar), or marketing technology stacks; Braze experience is a plus.

  • Ability to identify process inefficiencies and develop structured, scalable solutions.

  • Excellent written and verbal communication skills, and you can explain technical concepts clearly to non-technical teammates.

  • Basic project management skills; organized, proactive, and reliable with deadlines.

  • Experience with segmentation, A/B testing, and performance reporting.

  • Strong experience in data visualization tools and SQL.

  • Ability to prioritize and manage multiple tasks simultaneously 

  Educational & Professional Experience

  • Background in computer science, analytics, engineering, AI, and/or related fields.

  • Exposure to business, marketing, finance, or other related fields

  • Previous internships or academic projects involving campaign management, marketing analytics, and content creation preferred.

  • Professional, academic or personal projects that demonstrate an ability to creatively use AI to create efficiencies.

Preferred Qualifications:

• Experience building AI-first platforms or internal products from scratch, including early architectural decisions.

• Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.

• Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine-tuning strategies for domain-specific applications.

• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.

• Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).

• Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.

• Familiarity with cloud-native development using AWS.

• Understanding of prompt engineering, retrieval-augmented generation (RAG), and LLM application patterns.

• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.

• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).

• Experience with Golang is a plus (or willingness to learn).

• Experience with Braze or similar consumer facing CRM platforms and/or various B2C digital marketing channels like affiliate, CTV, paid social, paid search, GEO/SEO, DSP.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.

• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things

• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.

• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is 2,500 - 3,333 USD  per month (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer I who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer I on the Applied AI team, you will contribute to the development of platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered features, developing intelligent automation and agentic systems, and embedding AI solutions into customer-facing products, internal tools, and operational workflows.

You will work closely with senior engineers and cross-functional teams to identify opportunities where AI can drive meaningful impact—whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers early in their AI careers who want hands-on exposure to production-grade AI systems, with opportunities to grow into greater ownership and technical leadership over time.

What You'll Do:

• Contribute to the design and development of AI-powered platforms and systems, working alongside senior engineers on complex initiatives.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Build AI-driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity.
• Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally
• Integrate AI capabilities into customer-facing products, internal tools, and operational workflows.
• Build full-stack components spanning backend services, APIs, data layers, and frontend interfaces.
• Translate business and operational problems into maintainable, AI-enabled technical solutions with guidance from senior team members.
• Apply systems thinking to ensure reliability, performance, and security across platforms.
• Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions.
• Participate in production support and incident response for team-owned systems, learning operational best practices.
• Engage in code reviews and knowledge sharing to continuously improve skills and contribute to team growth.
• Familiarity with Braze or similar consumer facing CRM platforms and/or various B2C digital marketing channels like affiliate, CTV, paid social, paid search, GEO/SEO, DSP.

What We'll Look For:

• 1–3 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Exposure to building AI-powered platforms or products, including contributing to architectural decisions.
• Foundational knowledge of core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, and model evaluation.
• Familiarity with transformer architectures (BERT, GPT, etc.) and basic understanding of attention mechanisms, tokenization, and fine-tuning concepts.
• Exposure to embeddings and vector representations, including text embeddings and similarity search concepts; interest in vector databases (Pinecone, Weaviate, pgvector, or similar).
• Familiarity with NLP techniques such as text classification, named entity recognition, or semantic search.
• Familiarity with real-world agentic frameworks workflow engines (e.g., in-house automation platforms, langchain/graph, n8n, Make, or similar), with a solid understanding of how they work under the hood.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with cloud-native development using AWS.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is $3,333 - $6,000 per month (Gross in USD)

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer II who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer II on the Applied AI team, you will take on end-to-end ownership of complex platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered platforms from scratch, developing intelligent automation and orchestration systems, and embedding proprietary AI solutions directly into customer-facing products, internal tools, and operational workflows.

You will operate in highly ambiguous problem spaces, working closely with product, engineering, and operations teams to identify opportunities where AI can drive meaningful impact — whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers ready to move beyond scoped execution and into leading solutions: shaping architecture, driving implementation, and ensuring that what is built is reliable, scalable, and genuinely useful for both external users and internal teams.

What You'll Do:

• Lead the design, development, and ownership of AI-powered internal platforms and systems, including initiatives built from the ground up with a focus on Marketing.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Design and implement AI-driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
• Embed AI capabilities into customer-facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
• Build full-stack systems spanning backend services, APIs, data layers, and frontend interfaces.
• Translate ambiguous business and operational problems into scalable, maintainable, AI-enabled technical solutions.
• Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
• Collaborate closely with engineers, teams, and stakeholders across the company to identify high-impact opportunities and drive adoption.
• Participate in production support and incident response for owned systems, helping define and uphold reliability and operational best practices.
• Mentor AI team members through code reviews, design feedback, and hands-on guidance, raising the overall quality bar of the team.

What We Look for:

• 3–5 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Experience building AI-first platforms or internal products from scratch, including early architectural decisions.
• Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.
• Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine-tuning strategies for domain-specific applications.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).
• Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.
• Familiarity with cloud-native development using AWS.
• Understanding of prompt engineering, retrieval-augmented generation (RAG), and LLM application patterns.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).
• Experience with Braze or similar consumer facing CRM platforms and/or various B2C digital marketing channels like affiliate, CTV, paid social, paid search, GEO/SEO, DSP.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The Mission

This is a senior role for someone who leads from both directions at once — deeply technical on customer engagements, and fully accountable for the growth and performance of a team of ML engineers and architects. You will report to the Director of AI/ML.

You own hiring, development, and team health alongside leading complex customer engagements, shaping architecture, and driving pre-sales. Both parts of this job are real and ongoing. The right candidate will find energy in that combination, not tension.

Your Assignment

Leading Your Team

• Hire and build: Set the technical bar for ML roles on your team, lead or oversee technical assessments, and make hiring decisions you can stand behind. Build a team that raises the practice's overall standard.
• Develop people: Run regular structured 1:1s, provide candid feedback at meaningful milestones, and actively invest in each person's growth — whether they are early in their career or highly experienced.
• Manage performance: Recognize strong contributors and address performance gaps directly and early. Partner with HRBPs and the Director of AI/ML when situations require a structured path, and advocate for your team when they deserve it.
• Stay close to staffing: Understand how your team is utilized across engagements, keep the staffing team informed of each person's skills evolution and preferences, and ensure people are placed in work that stretches them appropriately.

Strategic Advisory

• Lead ML assessments: Evaluate customer environments end-to-end — infrastructure, data pipelines, model lifecycle, and organizational readiness — and produce recommendations that drive executive decisions and open the door to the next engagement.
• Shape architecture: Serve as the senior technical authority on engagements, setting architectural direction, ensuring technical quality across the team, and making the calls that matter when tradeoffs are hard.
• Advise on ML operations: Help customers build ML systems they can actually own and sustain — translating MLOps, LLMOps, and production monitoring complexity into standards their engineering teams can execute and their leadership can act on.
• Drive pre-sales: Partner with sales and solutions teams during scoping and proposal phases, contributing the technical depth needed to scope work accurately and give prospects confidence in Caylent's ability to deliver.

Hands-On Delivery

• Lead engagements end-to-end: Drive architecture and solution design from kickoff through delivery — setting technical direction, unblocking the team on hard problems, and ensuring the work meets Caylent's quality standards.
• Own the technical relationship: Depending on the engagement, you are either the primary client contact owning all architect-level outcomes, or the senior technical authority providing oversight across the team. The expectation is the same in both cases — you are the person the engagement depends on technically.

Growing the Practice

• • Raise the bar internally: Mentor engineers and architects through real work, contribute to technical interviews, and build reference architectures and accelerators that make the broader ML practice better.

Your Qualifications (non-negotiables)

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Demonstrated people management experience — hiring, performance calibration, career development, and the ability to have difficult conversations directly and constructively.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether classical ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training — combined with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop patterns on AWS.
• Proven ability to operate independently in complex, ambiguous customer environments — navigating competing priorities, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Fluency in AIOps patterns — designing agentic workflows for anomaly detection, automated root cause analysis, and remediation across observability platforms — and the ability to translate AI operations outcomes into measurable business value for customers.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

• ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI
• AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)
• Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts
• AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly
• Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue
• Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate
• Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama
• MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness
• LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation
• Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

Benefits

• Pay in USD
• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

The Opportunity

This is a senior technical client leadership role that blends deep hands-on ML expertise with strategic advisory and consulting skills. You will be the most experienced ML voice across a diverse and expanding book of customer engagements — from early-stage companies bringing ambitious ML ideas to market, to established enterprises modernizing how they build and operate AI systems on AWS.

You will shape strategy, influence architecture, and leave every team you touch better than you found it. You bring the scientific depth to design and evaluate models rigorously, the engineering depth to architect production ML systems at scale, and the consulting instincts to translate both into business value for customers.

If you have led the hard conversations, shaped the architecture decisions that mattered, and built the things others benchmark against — and you are looking to do that across a growing portfolio of varied and interesting customers — this is the role for you.

What You'll Do

• Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement.
• Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work.
• Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities.
• Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative.
• Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain.
• Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers.
• Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership content.

What You Bring

The non-negotiables

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether traditional ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards and decisions that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization (quantization, vLLM), and distributed training (DeepSpeed, FSDP) — combined with RAG and agentic system design, including multi-agent architectures, event-driven workflows, MCP integration, and human-in-the-loop patterns on AWS. Technical authority to prescribe the right approach and set architectural standards that teams can execute against.
• Proven ability to operate independently in complex customer environments — navigating ambiguity, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Hands-on experience designing and deploying SRE agents and AI-driven operations workflows in production — spanning automated incident detection, triage, and remediation — with the ability to integrate across observability platforms and translate AI operations outcomes into measurable business value.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI

AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)

Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts

AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly

Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue

Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate

Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama

MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness

LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation

Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

About the Role

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results. You will bridge the gap between technical innovation and real-world business challenges by applying advanced statistical and machine learning techniques to build predictive models and derive actionable insights.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading complex technical projects with multi-team impact.
• Advanced ML & Statistics: Expert capability in designing end-to-end ML systems for complex problems (including imbalanced data and concept drift), applying advanced statistical methods (mixed models, survival analysis, Bayesian approaches), and demonstrating a deep understanding of causal inference techniques, experimentation design (A/B testing, MABs), and deep learning architectures for unstructured data (e.g., NLP, Computer Vision).
• Core Technology Stack: Expertise in Python (including libraries like Pandas and NumPy) or R, proficiency with cloud platforms and their data/ML services (e.g., AWS Sagemaker, GCP Vertex AI, Azure ML Services), experience with big data technologies (e.g., Spark, Hadoop), and familiarity with MLOps tools (e.g., Kubeflow, MLflow, Docker).
• Business Immersion: Proven ability to immerse in operations to acquire deep domain expertise, thinking like an insider to translate seamlessly between business needs and engineering solutions.
• Full-Stack Agility: Ability to build complete applications rapidly across any technology stack, selecting the right tools to balance technical debt with delivery speed.
• Data Strategy & Integration: Experience architecting scalable data strategies across diverse teams and complex enterprise landscapes. This includes defining data governance policies, mastering data quality frameworks, building robust integration solutions for undocumented schemas and disparate systems, and driving the adoption of modern data warehousing and lakehouse architectures.
• AI Evaluation & Governance: Experience leading AI governance initiatives, creating evaluation standards, and training teams on rigorous AI verification and risk management.
• Rapid Prototyping: Proficiency in leading rapid delivery initiatives using a prototype-first approach to validate solutions quickly before scaling.
• Problem Discovery: A track record of seeking out undefined problems, embedding with users to discover latent needs, and turning ambiguity into clear problem statements.
  
  

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model

Santex is a US-based global company founded in 1999, with 26 years of experience in the software industry. Headquartered in California with offices in Córdoba, Argentina, its talent network spans over 18 countries thanks to its flexible, remote-first culture. Santex specializes in custom enterprise software development, operating through Hubs that include eCommerce, BIM, Mobility, Content Delivery, Integration, Web & Mobile Development, Cloud Computing, Artificial Intelligence (AI), Data Science, IT Consulting, and Services. The company is committed to making a positive impact across three dimensions: economic, social, and environmental.

Job description:
We are seeking an AI Data Engineer to design, build, and scale the data foundations that power AI, advanced analytics, and natural language interfaces across a global Quick Service Restaurant (QSR) enterprise. This is a high-impact role at the intersection of data engineering and applied AI, where the pipelines you build become the building blocks for use cases like automated insight generation, conversational analytics, and intelligent decision support at restaurant scale. A core focus of this role is data ingestion from POS systems and back-office vendor platforms spanning labor, inventory, finance, and supply chain. You will ensure reliable, standardized, and scalable ingestion of high-volume, multi-source data into the enterprise data platform, transforming fragmented operational data into AI-ready assets. You will also play a critical role in connecting raw data to business meaning, supporting governed KPI definitions and AI-driven context engineering through a robust semantic layer that enables both human analysts and AI agents to query, reason over, and act on trusted data.

Key Responsibilities – Data Ingestion & Integration (POS & Back Office)
- Design and build ingestion pipelines for POS systems across global markets (transactions, orders, payments, speed of service)
- Integrate data from back-office vendor systems (labor scheduling, inventory, supply chain, finance)
- Handle diverse ingestion patterns (batch, streaming, APIs, file-based ingestion)
- Normalize and standardize data across vendors, regions, and brands
- Ensure data freshness, completeness, and consistency across all ingestion pipelines
- Manage vendor-specific schemas and evolving data contracts

Key Responsibilities – Data Platform & Pipeline Engineering
- Build scalable ELT/ETL pipelines using modern tools (DBT, Airflow, etc.)
- Support real-time and batch processing for operational and analytical use cases
- Optimize ingestion pipelines for performance, reliability, and cost
- Ensure high availability across global data workloads

Key Responsibilities – Semantic Layer Enablement
- Build data models supporting standardized KPIs (same-store sales, speed of service, traffic, labor productivity)
- Align ingested raw data with business-friendly semantic abstractions
- Support both governed (manual) and AI-driven semantic approaches

Key Responsibilities – Metadata & Context Engineering
- Capture metadata, lineage, and schema details from ingestion pipelines
- Enable AI systems using structured context (metadata, lineage, example queries)
- Ensure AI systems can reliably interpret POS and operational data

Key Responsibilities – Governance & Data Quality
- Implement validation and monitoring for ingestion pipelines
- Ensure data accuracy across POS and vendor systems
- Support governance for consistent metric definitions across regions
- Maintain versioning and schema evolution processes

Required Qualifications
- 5+ years of experience in data engineering
- Strong SQL and Python skills
- Experience building ingestion pipelines from APIs, streaming, and batch sources
- Experience with POS or operational data systems preferred
- Experience with cloud data platforms and modern data stack

Preferred Qualifications
- Familiarity with Agentic development tools such as Codex, Cursor or Claude Code
- Experience in QSR or retail environments
- Experience integrating vendor systems (labor, inventory, finance)
- Familiarity with semantic layers and metadata tools
- Experience enabling data for AI/LLM use cases

Success Metrics
- Reliability and latency of POS and back-office data ingestion
- Standardization across vendor data sources
- Reduction in data inconsistencies
- Improved downstream analytics and AI performance

Summary
This role ensures that high-quality, standardized data from POS and back-office systems flows into the enterprise platform—enabling trusted analytics, semantic consistency, and AI-driven insights at global scale.

Location: LATAM

Santex is a US-based global company founded in 1999, with 26 years of experience in the software industry. Headquartered in California with offices in Córdoba, Argentina, its talent network spans over 18 countries thanks to its flexible, remote-first culture. Santex specializes in custom enterprise software development, operating through Hubs that include eCommerce, BIM, Mobility, Content Delivery, Integration, Web & Mobile Development, Cloud Computing, Artificial Intelligence (AI), Data Science, IT Consulting, and Services. The company is committed to making a positive impact across three dimensions: economic, social, and environmental.

Job Description:

We are seeking an AI Enablement Engineer to design and scale the semantic layer that turns raw restaurant data into a shared language for AI, analytics, and decision-making across a global Quick Service Restaurant (QSR) enterprise. This is a foundational role in our AI strategy: the semantic layer you build is what makes natural language analytics, automated reporting, and intelligent AI agents possible at enterprise scale. Your focus is bridging business meaning and data, ensuring that AI systems, analytics platforms, and end users consistently interpret critical metrics like same-store sales, speed of service, traffic, and labor productivity in a standardized, governed way. When an AI agent or a franchisee asks "how did my restaurant perform last week," the accuracy and trust of that answer starts with your work.
You will define and operationalize a hybrid semantic layer strategy that combines governed, metadata-driven models with AI-powered context engineering to enable scalable, accurate, and self-service insights across restaurants, corporate teams, and franchisees, unlocking the building blocks for conversational analytics and autonomous AI workflows.

Key Responsibilities – Semantic Layer Strategy & Architecture

• Define and implement an enterprise semantic layer that standardizes metric definitions and aligns business questions to data
• Establish canonical definitions for core KPIs (e.g., same-store sales, speed of service, traffic, labor productivity)
• Design mapping between business concepts and underlying data models across systems (POS, digital, supply chain, finance)
• Provide structured metadata to power AI systems, copilots, and analytics tools. 

Key Responsibilities – Hybrid Semantic Model Implementation

• Build and maintain manual, metadata-driven semantic models for high-criticality domains (finance, core KPIs, franchise reporting)
• Enable AI-driven context engineering for exploratory analytics, operational insights, and ad-hoc queries
• Define how both approaches coexist in a unified architecture

Key Responsibilities – Tooling & Platform Enablement

• Implement semantic layer tooling (DBT, semantic views, YAML/Markdown metadata, data catalogs like Atlan)
• Enable downstream consumption by BI tools, APIs, and AI applications
• Create reusable abstractions and templates to scale globally

Key Responsibilities – AI & Context Engineering Integration

• Enable AI systems (LLMs, agents, copilots) to leverage semantic metadata
• Support context engineering using data lineage, metadata, example queries, and repository context
• Improve AI reliability by grounding outputs in governed definitions

Key Responsibilities – Governance & Data Quality

• Establish governance processes for metric definitions
• Ensure alignment across regions, brands, and franchise reporting
• Implement validation, versioning, and change management
• Define guardrails to prevent inaccurate analytics outputs

Key Responsibilities – Adoption & Enablement

• Partner with business and technical teams to drive adoption
• Educate stakeholders on standardized metrics and self-service analytics
• Provide documentation, playbooks, and training

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Analytics, or related field
• 5+ years of experience in data engineering, analytics engineering, or AI/ML systems
• Strong experience with semantic modeling or analytics engineering
• Proficiency in SQL and Python
• Experience with DBT and modern cloud data platforms
• Understanding of APIs and distributed systems

Preferred Qualifications

• Experience in QSR, retail, or franchise environments
• Experience with semantic/metrics layers
• Familiarity with data catalogs (e.g., Atlan)
• Experience with generative AI, LLMs, and context engineering
• Knowledge of data lineage and governance frameworks

Additional Expectations

• Design and maintain CI/CD pipelines, including automated builds, testing, and deployment of solutions
• Develop and execute functional and regression test suites to validate metric accuracy, data completeness, and semantic model behavior across environments
• Implement automated data and code quality checks and integration tests within the deployment pipeline to catch issues before they reach production
• Apply software engineering best practices including version control, code review, branching strategies, and environment promotion (dev/staging/prod) to all semantic layer and metadata assets
• Monitor platform performance, troubleshoot pipeline failures, and maintain observability across semantic layer infrastructure using logging, alerting, and health checks
• Define and manage infrastructure as code (e.g., Terraform, CloudFormation) for data platform resources, ensuring reproducible and auditable environment provisioning across development, staging, and production
• Implement and maintain role-based access controls, secrets management, and security policies across semantic layer tooling, data platform resources, and API integrations to ensure compliance with enterprise security standards

Key Skills & Competencies

• Systems thinking across data, analytics, and AI
• Ability to translate business metrics into data models
• Balance governance with scalability
• Strong stakeholder management
• Clear communication of complex concepts

Success Metrics

• Adoption of standardized metric definitions
• Reduction in reporting inconsistencies
• Improved accuracy of AI-generated insights
• Increased self-service analytics usage
• Faster time-to-insight

Reporting Structure

• Reports to: VP / Director of Data, AI, or Platform Engineering
• Works closely with: Data Engineering, Analytics, AI/ML, Finance, Operations, Franchise teams

Summary
The AI Enablement Engineer (Semantic Layer) establishes a shared language between business and data. By combining governed semantic models with AI-driven context understanding, this role enables scalable, accurate, and trusted analytics and AI across a global QSR enterprise.

Location: LATAM

The Role:

• We are looking for a Tech Enablement Engineer to join our B2B Operations team, where you will play a key role in building and optimizing the internal technology that powers CookUnity’s B2B initiatives.
• In this role, you’ll work closely with the Tech Enablement Lead (to whom you will report) and collaborate with stakeholders across operations, product, and engineering to deliver innovative solutions.
• You’ll be developing end-to-end automation workflows, creating internal web/mobile applications, maintaining custom hardware setups (like our smart fridge prototypes), and managing integrations with third-party software.
• This is a great opportunity for a mid-level engineer who enjoys working on a wide range of technologies – from scripting and full-stack development to IoT devices and AI tools – all with the goal of improving efficiency and enabling growth.
• If you are enthusiastic about solving complex operational problems with creative tech solutions, and you thrive in a cross-functional environment, then this role will be a perfect fit.

Responsibilities:

• Build & Optimize Automations: Ideate, develop, and maintain end-to-end automation workflows to streamline internal processes. This includes using low-code tools (like n8n) and custom scripts (SQL, Google Cloud Functions, Apps Script, Node.js/Python) to connect APIs, databases, and services, reducing manual work for our teams.
• Full-Stack Internal Tools: Create and enhance internal applications for web and mobile. You’ll work with modern front-end frameworks (e.g. React/Next.js) and back-end code (Node.js, Python, SQL) to build tools that improve our Ops and B2B services. You will also set up CI/CD pipelines (GitHub Actions or similar) to deploy these tools efficiently.
• Hardware (IoT): Contribute to the development and upkeep of custom hardware solutions, such as our Raspberry Pi–powered smart fridges. This involves working with electronic locks, sensors, cameras, and integrating computer vision capabilities. You’ll help ensure these devices are remotely accessible, regularly updated, and functioning reliably in the field.
• Third-Party Integrations: Manage and improve integrations with external software used by the team (such as Zendesk, Aircall, Jira, etc.). This could mean configuring integrations, writing custom API wrappers or webhooks, and ensuring data flows smoothly between CookUnity’s systems and these platforms.
• AI Tools & Agents: Experiment with and build AI-driven tools to support the team’s objectives. For example, you might prototype AI agents or chatbots to assist with support tasks or data analysis, leveraging frameworks or APIs for natural language processing.
• Marketing & CRM Support: Work closely with our Marketing and Data teams to automate their workflows. This can include connecting marketing automation platforms, writing scripts to handle data ingestion or transformation for Salesforce, and implementing validation rules or triggers in our CRM to maintain data integrity. You’ll also help create custom Salesforce dashboard components or integrations as needed.
• Documentation & Handover: Document all your solutions and processes clearly. Because Tech Enablement often pioneers new tools and workflows, you will ensure that everything built is well-documented and can be easily handed over or transitioned to Product/Engineering teams for long-term ownership. You’ll create how-to guides, architecture diagrams, and operational runbooks to facilitate smooth knowledge transfer.

Minimum Requirements:

• 3+ years of experience in software development, with hands-on exposure to a broad range of technologies.
• Proficiency in coding with JavaScript/TypeScript and Python. You have built scripts or services in these languages and are comfortable with both front-end and back-end development.
• Experience developing web applications using modern frameworks (for example, React/Next.js on the front end and Node.js or Python on the back end).
• Solid understanding of RESTful APIs and webhooks, and experience integrating with third-party APIs or SDKs.
• Familiarity with SQL databases and ability to write and optimize SQL queries.
• Experience with automation workflows or low-code platforms (such as n8n, Zapier, or similar), or demonstrated ability to design custom automation scripts to connect various systems.
• Basic knowledge of cloud services and DevOps: comfortable deploying apps or functions on cloud platforms (e.g. Google Cloud Functions, AWS Lambda) and using CI/CD pipelines for version control and deployment.
• Exposure to working with hardware or IoT projects (even if hobbyist): you can configure devices, install OS/software on a Raspberry Pi (Linux), and troubleshoot connectivity or sensor issues.
• Strong problem-solving and troubleshooting skills across different domains (software, hardware, integrations).
• Fluent English communication skills (verbal and written). Ability to effectively communicate technical ideas to non-technical team members and collaborate across teams in English.
• Fluency with AI engineering tools.

Preferred Requirements:

• Experience with workflow automation tools like n8n (self-hosted or cloud), Zapier, or HubSpot workflows, especially in an operations context.
• Hands-on experience with Raspberry Pi or Arduino projects, and familiarity with protocols (GPIO, I2C, etc.) or using camera modules for computer vision.
• Knowledge of Salesforce (or other CRM) data structure and APIs, including building data pipelines or using ETL tools to feed data into Salesforce, and understanding of Salesforce Process Builder/Flow or validation rules.
• Familiarity with Google Cloud Platform services (Firestore, Cloud Functions, etc.) and/or other cloud providers (AWS, Azure) for building and hosting applications.
• Understanding of AI/ML concepts or prior experience integrating AI APIs (e.g., OpenAI GPT) into applications or bots.
• Experience with customer support and marketing tools (e.g., Zendesk, Aircall, email marketing platforms) and implementing tech solutions around them.
• Comfortable working in a fast-paced startup environment where you’ll have to wear multiple hats and coordinate with diverse teams.
• A self-starter attitude with curiosity and willingness to continuously learn new technologies and tools.

Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we’re looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we’d love to connect!

Benefits

💸 Get paid in USD!

🗺 Work remotely: design the life that you want.

⛱ Enjoy 15 business days of vacation each year from the start date.

🎄16 fully paid Argentinean holidays.

🩺 Healthcare Benefit: Monthly stipend to use in your preferred healthcare provider.

🗓️ 5-year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical.

🐣 Paid family leave.

🕯 Compassionate Leave: 3-5 days each time the need arises.

🧘🏽‍♀️ Customize the benefits that suit your needs! Access a range of perks tailored to you, including learning opportunities, wellness memberships, delivery apps, and more through our comprehensive benefit platform.

🧑‍🏫 Personalized English coach.

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

As a DevSecOps Engineer, you will be the link between development, operations, and security. You will work with delivery teams to embed security controls and best practices into pipelines, automate compliance, and ensure our platforms are reliable, resilient, and secure. You will participate in architecture discussions, help detect and remediate vulnerabilities, and continuously improve our DevSecOps practices. 

You will work in a multidisciplinary environment with engineers across the globe, ensuring that security does not block innovation but rather accelerates it.

.You are someone with 5+ years of experience in Security Engineering, or DevSecOps, preferably in large-scale, customer-facing platforms. You have deep expertise in automation, cloud-native security, and CI/CD. You combine technical leadership with strong communication skills, and you are comfortable working in global and multicultural teams. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role responsibilities

• Define and implement enterprise-wide DevSecOps standards, patterns, and guardrails. 

• Design and build security automation mechanisms such as secure CI/CD pipelines with integrated SAST, DAST, SCA, IaC scanning, and container security. 

• Design and Implement cloud-native security tooling and platforms. 

• Lead security reviews, audits and threat modeling for high-impact platforms and projects. 

• Guide teams and promote security awareness on secure coding, vulnerability remediation, and cloud security best practices, acting as a Security Subject Matter Expert. 

• Automate compliance and governance requirements at scale. 

• Participate in and lead security incident lifecycle, including RCA, remediation, postmortem analysis, and resilience improvements. 

• Mentor and coach DevOps/DevSecOps engineers across teams. 

• Advocate for and implement practices to reduce toil and scale security automation. 

• Define and/or conduct regular vulnerability assessments and manage remediation efforts 

• Ensure our clients' systems and applications meet regulatory and organizational security standards (e.g. NIST, ISO, SOC 2, PCI DSS, GDPR, etc.) 

• Help define and implement monitoring solutions and participate in incident response and remediation as needed 

• Work closely with development, ops, and security teams to ensure secure delivery of software 

Must have qualifications

To be considered for this role, you must meet the following essential qualifications: 

• You have led DevSecOps initiatives in enterprise or high-traffic production environments. 

• You have strong experience with cloud security (Mostly Azure). 

• You are proficient in CI/CD tooling. 

• You have advanced knowledge of container security and orchestration (Docker, Kubernetes, AKS). 

• You have hands-on experience with security scanning tools (Snyk, SonarQube, Trivy, Aqua, Prisma, Checkov, etc.). 

• You have implemented monitoring and observability solutions with a security lens (New Relic, Prometheus, Grafana, ELK). 

• You are fluent in at least one scripting/programming language (Python, Go, Bash, etc.) for automation. 

• You are experienced in IAM, secrets management, and zero-trust principles. 

• You are a natural mentor, able to upskill and guide other engineers. 

Nice to have qualifications  

• Strong communication and presentation skills 
• Accountability, collaboration, and time-management skills 
• Strong desire to learn more about business every day 

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a Full time position based in Buenos Aires

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts 

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.