1175 - Applied AI Engineer

Role overview Build and improve AI features that address meaningful product needs, from early technical scoping through production release. The role combines hands-on software engineering, LLM and agent development, retrieval over data, and ongoing evaluation of how well systems perform.

Responsibilities - Partner with product teams to define technical approaches and measures of success for AI opportunities. - Develop and launch LLM-powered features and agents, including workflows that automate client data onboarding. - Build and maintain retrieval and RAG capabilities on top of data foundations prepared by data engineers. - Create evaluation processes and production monitoring for quality, cost, and response time, then use findings to improve systems. - Refine AI capabilities used directly by customers.

Requirements - Mid-to-senior software engineering experience, including production delivery of LLM features or agents. - Production programming experience in Python or Node.js/TypeScript; Python is preferred. - Practical experience with prompt and tool design, structured outputs, retrieval/RAG, and agent orchestration. - Ability to evaluate AI systems using representative test data, automated checks, human review, and production monitoring. - Experience with AWS or another enterprise cloud, including AI services; AWS Bedrock is preferred. - Daily use of agentic AI coding tools and experience integrating shared AI workflows into team development and CI/CD. - Strong English and communication skills.

Nice to have - Familiarity with agent tool protocols such as MCP, SQL, cloud data warehouses such as Snowflake, or infrastructure as code such as Terraform. - Exposure to energy, utilities, or sustainability data.

Benefits and work setup - Remote, full-time contract for candidates based in Latin America, with a 40-hour workweek. - Listed monthly compensation is USD $4,000–$5,000, depending on experience and skills.