AI Engineering Lead

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

📋 Description

• Oversee comprehensive project delivery with established governance and effective communication with stakeholders.

• Guide junior engineers while also contributing to proposals and new business opportunities.

• Specify suitable AI system functionalities and convey risks and trade-offs to clients.

• Create and develop production-ready RAG systems, agentic frameworks, and LLM-driven solutions.

• Utilize advanced prompt engineering techniques.

• Conduct feasibility assessments covering prompting, RAG, fine-tuning, and traditional ML.

• Develop evaluation frameworks utilizing LLM-as-a-judge methods, custom metrics, and go/no-go criteria.

• Execute structured experiments involving prompts, retrievers, chunking strategies, and models.

• Detect and classify model failure modes.

• Construct scalable inference infrastructure and CI/CD pipelines for AI/ML models.

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

• Design APIs, microservices, and orchestration layers optimized for latency, cost, and reliability.

⛳️ Requirements

• Proficient in Python at an expert level.

• Strong practices in Git.

• Experience in ML/LLM versioning.

• Solid cloud experience with AWS, Azure, or GCP, with a preference for Azure.

• Experience in containerization and orchestration.

• Hands-on experience with RAG involving chunking, embeddings, retrieval, reranking, and evaluation.

• Demonstrated MLOps/LLMOps experience using tools such as MLflow, Weights & Biases, or similar platforms.

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

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

• Strong communication abilities with engineering teams and senior stakeholders.

• Preferred experience with Databricks MLOps, LLM fine-tuning, agentic GenAI systems, Infrastructure as Code, AI-service security and observability, classical ML, and contributions to open-source projects.

• Advanced English proficiency is required for effective communication with global teams.

• A minimum of 6 years of experience in developing and deploying AI solutions in production settings, including RAG, agentic systems, and MLOps/LLMOps.

🏝️ Benefits

• Certifications in AWS, Databricks, and Snowflake.

• Access to AI learning pathways.

• Study plans, courses, and additional certifications customized for the role.

• Access to Udemy Business.

• English language lessons.

• Opportunities for travel to industry conferences and client meetings.

• Career development plans and mentorship programs.

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

• Company-provided equipment.

• Flexible working arrangements.

• Additional benefits may differ based on location within LATAM.