Senior, AI Engineer - AA, Remote: Colombia - Costa Rica, Fulltime, Digital Product Development

We are looking for a Senior Generative AI Engineer to design, build, and deploy production-grade generative AI solutions for enterprise clients. This role requires deep hands-on experience with modern LLM-based systems and the ability to take projects from concept to production in complex, real-world environments.

You’ll work closely with cross-functional teams to solve ambiguous problems, design scalable AI architectures, and deliver impactful solutions that meet enterprise standards.

Responsibilities

Design, develop, and deploy generative AI systems in production environments.

Build and maintain robust evaluation frameworks to assess model performance, reliability, and safety.

Design and optimize Retrieval-Augmented Generation (RAG) pipelines.

Work with multiple LLMs, model providers, and AI frameworks to select the best solution for each use case.

Develop agentic and multi-agent systems to solve complex workflows and reasoning tasks.

Own the full lifecycle of enterprise AI projects, from discovery and prototyping to deployment and iteration.

Collaborate closely with data engineers, backend engineers, product managers, and clients.

Contribute to best practices, architecture decisions, and technical standards across AI initiatives.

Required Qualifications

5+ years of industry experience, including 2+ years focused on generative AI systems
(10+ years total experience strongly preferred).

Strong proficiency in Python.

Proven experience delivering generative AI solutions to production in an enterprise setting.

Evaluation frameworks and AI testing strategies

RAG system development and optimization

Agentic and multi-agent architectures

Familiarity with a variety of LLMs, tools, and AI frameworks.

Comfortable working end-to-end across the AI project lifecycle.

Strong problem-solving mindset; able to move forward amid ambiguity.

Collaborative, collegial, and delivery-focused.

Nice to Have

Experience with data engineering, SQL, and relational databases.

Experience building or deploying solutions on Azure.

Background working with enterprise-scale systems and clients.