---
title: "Lead Machine Learning Engineering"
company: "LATAM"
company_url: "https://www.remjobs.works/companies/latam"
url: "https://www.remjobs.works/job/latam-lead-machine-learning-engineering-8eba257b-ae08-4831-85cd-674a95ed662b"
apply_url: "https://job-boards.greenhouse.io/xebialatam/jobs/6181079004"
workplace: onsite
location: "Colombia"
employment_type: unspecified
seniority: lead
role: ai-machine-learning
region: latin-america
skills: ["aws", "azure", "docker", "llm", "python", "react", "sql", "terraform"]
date_posted: 2026-09-04T21:43:20.000Z
first_seen_by_remjobs: 2026-09-19T22:10:13.454Z
---

# Lead Machine Learning Engineering

**LATAM** · Colombia

Apply: https://job-boards.greenhouse.io/xebialatam/jobs/6181079004

## About the role

**Role Overview**

We are looking for a Senior AI Engineer who can design, build, and deploy production-ready AI solutions using modern Large Language Models (LLMs), AI agents, and cloud-native architectures. The ideal candidate combines strong software engineering fundamentals with hands-on experience building scalable AI applications, integrating foundation models, and delivering business value through Generative AI.

**Key Responsibilities**

- Design, develop, and maintain AI-powered applications using Large Language Models (LLMs) and Generative AI technologies

- Build AI agents and Retrieval-Augmented Generation (RAG) solutions to enable intelligent workflows and knowledge-based applications.

- Integrate leading AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or similar services.

- Develop scalable backend services and APIs using Python and modern frameworks such as FastAPI.

- Collaborate with frontend engineers to deliver end-to-end AI applications using technologies such as React.

- Design prompt engineering strategies to improve model accuracy, reliability, and user experience.

- Implement intelligent routing, semantic search, vector databases, and knowledge retrieval solutions.

- Deploy and manage cloud-native AI applications using AWS and Infrastructure as Code tools such as Terraform.

- Build and maintain CI/CD pipelines, containerized applications, and cloud infrastructure using Docker and DevOps best practices.

- Evaluate emerging AI frameworks, tools, and models to continuously improve platform capabilities.

- Collaborate with Product Managers, Architects, and Engineering teams to translate business requirements into scalable AI solutions.

- Mentor engineers and contribute to technical leadership, architecture discussions, and engineering best practices.

**Required Qualifications**

- 10+ years of experience in Software Engineering with recent hands-on experience building Generative AI solutions.

- Strong experience with Python and REST API development.

- Experience developing production AI applications using Large Language Models (LLMs).

- Hands-on experience with AI agent frameworks such as LangChain, CrewAI, or similar technologies.

- Experience implementing Retrieval-Augmented Generation (RAG) architectures.

- Experience integrating AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent services.

- Strong understanding of prompt engineering techniques and AI application design patterns.

- Experience developing scalable cloud applications on AWS.

- Experience with Docker, Terraform, CI/CD pipelines, and Infrastructure as Code.

- Experience with SQL and NoSQL databases.

- Familiarity with React or modern frontend technologies.

- Experience working within Agile software development environments.

- Strong understanding of software architecture, API design, and distributed systems.

- Experience working in cross-functional and multicultural teams.

**Working Style**

- Strong communication skills: able to clearly explain complex AI concepts to both technical and non-technical audiences.

- Proactive mindset: identifies opportunities for innovation and continuously explores new AI technologies.

- Ownership and accountability: takes responsibility for delivering reliable, scalable, and maintainable AI solutions.

- Collaborative attitude: works effectively across product, engineering, architecture, and business teams.

- Adaptability: thrives in a rapidly evolving AI landscape and embraces continuous learning.

- Attention to detail: prioritizes quality, security, observability, and responsible AI practices.

- Customer-oriented thinking: focuses on solving real business problems through practical AI solutions.

- Continuous learner: stays current with advancements in LLMs, AI frameworks, cloud services, and software engineering best practices

---

Source: LATAM's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/latam-lead-machine-learning-engineering-8eba257b-ae08-4831-85cd-674a95ed662b