Senior IA Engineer

This is a fully remote position, open to applicants in Argentina, +2 more countries.

📋 Description

• Develop AI-powered tools, internal assistants, and copilots throughout the Software Development Life Cycle (SDLC), encompassing code generation, code reviews, testing, documentation, and Infrastructure as Code (IaC) generation.

• Explore, benchmark, and implement Generative AI solutions like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and GitHub Copilot to enhance delivery pipelines, shorten lead time, and improve system reliability.

• Create prototypes of AI-enhanced platform features, including cost-aware autoscaling, predictive incident resolution, and automated root cause analysis within DevOps settings.

• Collaborate with Platform, Site Reliability Engineering (SRE), and DevOps teams to integrate intelligent automation into the Internal Developer Platform.

• Work alongside engineering leadership to pinpoint operational challenges and experiment with innovative AI methodologies.

• Share knowledge through workshops and internal presentations.

• Design, benchmark, and implement Generative AI-driven solutions within internal developer platforms and infrastructure workflows.

⛳️ Requirements

• Advanced proficiency in Docker and Kubernetes.

• Expertise in AWS or GCP cloud environments.

• Proficient in Terraform and Ansible for Infrastructure as Code.

• Strong hands-on experience with Python and Bash or Go.

• Practical experience in implementing Large Language Models and code-generation tools such as Codex, Claude, StarCoder, or the GPT family in real-world software development processes.

• Comprehensive understanding of the entire Software Development Lifecycle, including planning, testing, releasing, and monitoring.

• Strong familiarity with modern CI/CD automation systems.

• Research-oriented and inquisitive mindset towards evaluating emerging technologies.

• Excellent problem-solving abilities.

• Capacity to explain complex AI solutions to technical teams clearly.

• Preferred: experience with RAG architectures, prompt engineering, custom model fine-tuning, Internal Developer Platforms, published research, open-source contributions, or AI projects related to software quality, deployment safety, or observability.

🏝️ Benefits

• High-impact, strategic role influencing the future of AI-assisted engineering.

• Collaborative international environment with experienced technical leadership.

• Significant autonomy to research, prototype, and implement innovative Generative AI workflows.

• Long-term engagement offering competitive compensation and opportunities for growth.