Senior AI Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Oversee the complete project delivery process, ensuring governance, stakeholder engagement, and accountability for results.

• Develop and guide a high-performing AI engineering team.

• Set technical standards and foster a culture of quality and practicality.

• Take ownership of proposals and new business ventures.

• Assess technical feasibility and convey risks and trade-offs to clients.

• Determine the appropriate scope for AI systems and establish realistic expectations.

• Perform technical evaluations and architectural reviews.

• Direct the design and implementation of production-ready RAG systems, agentic frameworks, and LLM-driven solutions.

• Spearhead advanced prompt engineering, including instruction design, few-shot sets, structured outputs, and tool/agent prompts.

• Conduct feasibility evaluations across prompting, RAG, fine-tuning, and classical machine learning.

• Mentor engineers on AI system design and production deployment.

• Create evaluation frameworks, such as LLM-as-a-judge, recall@k, precision@k, and go/no-go gates.

• Lead systematic experiments involving prompts, retrievers, chunking strategies, and models.

• Institute practices for identifying and categorizing model failures.

• Establish standards for AI production reliability.

• Develop scalable inference infrastructure and CI/CD pipelines.

• Automate the MLOps/LLMOps lifecycle, encompassing tracking, versioning, deployment, monitoring, and retraining.

• Design APIs, microservices, and orchestration layers with a focus on latency, cost-efficiency, and reliability.

• Make infrastructure decisions that balance technical excellence with business efficiency.

⛳️ Requirements

• 5+ years of experience in building and deploying AI solutions within production settings.

• Proficient in Python at an expert level.

• Strong knowledge of Git practices.

• Experience with versioning and deployment in ML/LLM.

• Solid background in cloud services, particularly AWS, Azure, or GCP, with a preference for Azure.

• Familiarity with containerization and orchestration.

• Practical RAG experience that includes chunking, embeddings, retrieval, reranking, and evaluation.

• Demonstrated success in MLOps/LLMOps using tools like MLflow, Weights and Biases, or similar platforms.

• Strong skills in evaluation design, including metrics, dataset curation, and structured experimentation.

• Experience with event-driven architectures, APIs, and microservices.

• Ability to communicate clearly with engineering teams and senior stakeholders.

• Strong instincts for hiring and team building.

• Proven experience in mentoring.

• 2+ years of direct leadership or technical management experience.

• Advanced English proficiency required for communication with global teams and client leadership.

🏝️ Benefits

• Certifications in AWS, Databricks, and Snowflake.

• Access to AI learning paths.

• Tailored study plans, courses, and additional certifications relevant to the role.

• Access to Udemy Business.

• English lessons to enhance professional communication.

• Opportunities for travel to industry conferences and client meetings.

• Career development plans and mentorship programs.

• Special rewards for birthdays, work anniversaries, and other personal milestones.

• Company-provided equipment.

• Flexible working arrangements.

• Additional benefits may differ based on location in LATAM.