Detalle de la Oferta

Descripción de la Oferta

Resumen

What is the role?

The Cloud ML Architect is a Senior Manager technical leader responsible for designing, implementing, and managing secure, scalable, and cost-efficient machine learning operations in the cloud. The role requires hands-on technical depth in MLOps, Big Data, Security, and Generative AI architectures, optimize data platforms, and drive value through automation, governance, and innovation.

The architect acts as a bridge between IT, data science, and data engineering stakeholders, ensuring ML solutions are production-grade, operationally reliable, financially optimized, and aligned with enterprise goals.

Responsabilidades

What you'll do

- Define and lead the MLOps strategy, ensuring robust, automated, and scalable CI/CD/CT pipelines
- Oversee the end-to-end operation of ML solutions
- Integrate cloud-native security practices (IAM, encryption, auditing, secrets management) directly into ML workflows to ensure secure handling of data, models, and artifacts.
- Apply FinOps principles to monitor, govern, and optimize infrastructure and compute costs related to training, inference, and data pipelines.
- Design and operationalize Generative AI architectures on AWS, including the use of services such as Amazon Bedrock, SageMaker, and containerized LLMs.
- Develop and scale retrieval-augmented generation (RAG) pipelines using knowledge databases, enterprise search, and context-driven query mechanisms.
- Build agentic AI solutions using orchestration frameworks that enable LLMs to interact with internal tools, APIs, and third-party services for contextualized task execution.
- Optimize GenAI workloads across event-driven and batch pipelines, ensuring integration with APIs, endpoints, and broader enterprise ecosystems.
- Collaborate with IT teams to define and enforce standards, govern cloud environments, and ensure long-term sustainability of analytics platforms.

Calificaciones

Knowledge & Experience

- 5+ years of experience in telecom, enterprise IT, or consulting.
- Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field.
- Certifications in data management, cloud architecture, or DevOps/MLOps.
- Professional proficiency in English.
- Proven leadership in Big Data engineering and MLOps pipeline automation.
- Hands-on expertise in Python, Spark, SQL/NoSQL databases, and cloud-native warehousing.
- Deep familiarity with AWS, including services like SageMaker, CloudFormation, and IAM.
- Experience with CI/CD tools such as Jenkins, GitLab, and infrastructure as code (IaC) frameworks like Terraform or CloudFormation CDK.
- Understanding of SRE concepts, data lineage, and data catalog governance.
- Expertise in deploying and governing Generative AI and LLM-based systems using AWS tools and open-source models.
- Knowledge of agentic AI patterns, orchestration, and knowledge retrieval frameworks.

Skills & Abilities

- Strong leadership and interpersonal skills, capable of influencing and building partnerships across teams and geographies.
- Analytical mindset with the ability to translate business challenges into AI/ML solutions.
- Capable of articulating the value of data products and leading strategic discussions with technical and business stakeholders.
- The ability to bridge development and operations, enabling robust, governed, and performant ML workflows.
- Leadership experience aligning data, analytics, and IT strategies to deliver measurable business impact.
- A strong foundation in DevOps/MLOps, cloud-native security, and cost-efficient architecture design.
- The ideal candidate combines technical depth and innovative thinking to deliver enterprise-wide ML and GenAI platforms

Who We Are

We are the leading telecommunications company, connecting more than 40 markets in Latin America and the Caribbean with our video, broadband internet, telephony, and mobile services under the consumer brands, Flow, Liberty, Más Móvil, BTC, and Cabletica. We