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Open nowPosted 29 days ago

Lead Machine Learning Engineering

xebialatam1 open role

Where
Colombia
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Your applicationOpen nowLead Machine Learning Engineeringxebialatam · Colombia

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7.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 29 days ago

The posting

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
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