Senior AI Engineer

About the role

The is a pivotal role focused on elevating the technical capabilities and client impact of our data-driven solutions. In this position, you will own the full lifecycle of intelligent systems, from initial design through deployment and ongoing optimization. You will architect and construct production-grade AI agents and LLM-powered systems that address complex client challenges. If you identify as a data nerd, we invite you to connect and help us harness the power of Generative AI. This role is central to developing scalable data infrastructures that enhance decision-making for specific client needs.

Key facts

What you'll do

• Architect and construct production-grade AI agents and LLM-powered systems that serve e-commerce and retail applications.
• Develop multimodal data ingestion pipelines and structured extraction methods for unstructured sources to fuel advanced analytics.
• Integrate AI agents with tools, APIs, data sources, and MCP frameworks to create seamless operational workflows.
• Create evaluation and testing frameworks to improve accuracy and reduce hallucinations in generated outputs.
• Manage AI solutions across their entire lifecycle, from requirements gathering and architecture design to deployment and performance optimization.
• Design intake mechanisms that capture streaming data for demand planning forecasts and budget forecasting initiatives.
• Construct scalable pipelines that transform unstructured sources like audio, images, and documents into structured records ready for analysis.
• Generate evaluation frameworks that test model accuracy and implement robust hallucination control methodologies in production environments.
• Build integration layers connecting AI agents with tools, APIs, and MCP ecosystems to enhance functionality and interoperability.
• Develop testing suites that validate multimodal parsing for images, audio, and diverse document types to ensure reliability.
• Forge partnerships with e-commerce platforms to deploy recommendation models that drive user engagement and conversions.
• Ship optimization modules that enhance product categorization and quality control workflows for global clients.
• Coordinate deployment routines and oversee the implementation of LLM-powered systems worldwide with precision.
• Shape intelligent systems that drive high-level decision-making and optimize cloud platforms for maximum efficiency.
• Apply innovative solutions to streamline data processing and machine learning operations across all project phases.

Requirements

• Demonstrate advanced Python skills applied to the development of production-grade AI systems with a proven track record.
• Possess hands-on experience with LLMs, AI Agents, and Agentic AI architectures to design sophisticated solutions.
• Show familiarity with MCP, tool calling, and LLM orchestration frameworks to build integrated environments.
• Exhibit comprehensive knowledge of RAG architectures, knowledge graphs, and multimodal data parsing, including audio, images, and unstructured documents.
• Have experience in LLM evaluation, hallucination control, and testing methodologies to ensure high-quality outputs.
• Display the capacity to design and deploy scalable AI solutions in production environments that meet strict deadlines.
• Maintain advanced English and strong communication skills for effective collaboration with cross-functional teams.
• Commit to adhering strictly to the project scope and guidelines as defined in the practical notes section.
• Ensure all work aligns with the principles of data-driven insights, open collaboration, ownership, and positive mindset.
• Be prepared to engage in continuous learning and adaptation to emerging AI technologies and best practices.

Nice to have

The preferred items listed in the source include specific tools and methodologies that are highly valued. These consist of Amazon Web Services, Astronomer, and Databricks, which are integral to our technical stack. Certification in these platforms is considered a significant advantage for candidates. Experience with AWS, DBT, Google Cloud, Azure & Databricks is explicitly mentioned as being fully covered by the company. This demonstrates a commitment to professional development and skill enhancement in cloud technologies.

Practical notes

The engagement for this role is Remote

Latam, providing flexibility for candidates in the region. The location of the position is Argentina, which serves as the primary base for work activities. Candidates must be available to work within this geographic constraint. The compensation for this role is specified as 250000 USD on a yearly basis. There are no additional travel requirements, visa sponsorships, or specific deadlines mentioned in the source documentation. The role operates within a remote-first culture, allowing for a globally distributed team dynamic.