AI Engineer

Our client is building the next generation of intelligent software, where AI is expected to do more than generate a compelling response. The goal is to create dependable AI experiences that understand context, take action, and complete meaningful work for users. They are seeking an AI Engineer who can bridge machine learning, software engineering, infrastructure, and product development to turn rapidly advancing model capabilities into reliable production systems.

This Role Offers

• Fully remote opportunity available to candidates across the United States.
• High-impact work spanning machine learning, AI systems, infrastructure, and product development.
• End-to-end ownership from technical exploration through production deployment and continuous improvement.
• Opportunity to build practical LLM and agent-based systems using modern AI engineering technologies.
• Fast-moving, collaborative environment that values engineering judgment, technical quality, and demonstrated impact over pedigree.

Focus

• Build and ship production AI capabilities that connect model intelligence with dependable user experiences.
• Develop LLM systems involving prompting, tool use, contextual memory, agent workflows, and multi-step execution.
• Transform probabilistic model outputs into consistent, structured, and reliable application behavior.
• Own solutions across model integration, infrastructure, deployment, monitoring, and product delivery.
• Diagnose issues across model behavior, orchestration, infrastructure, application logic, and user experience.
• Improve AI performance across quality, latency, cost, scalability, and production reliability.
• Develop practical evaluation methods and use real-world signals to drive measurable system improvements.
• Collaborate across product and engineering to turn ambiguous challenges into scalable, production-ready solutions.

• Hands-on experience training, fine-tuning, integrating, serving, or deploying machine learning models.
• Strong software engineering skills with the ability to write clean, maintainable, production-quality code.
• Applied experience with LLM systems, including prompts, tools, memory, agents, inference, and evaluation.
• Ability to work across model, infrastructure, and product layers rather than exclusively within modeling or research.
• Strong Python skills and familiarity with frameworks such as PyTorch, JAX, or comparable ML technologies.
• Strong problem-solving and debugging skills in ambiguous, rapidly evolving technical environments.
• Demonstrated engineering judgment, end-to-end ownership, increasing technical scope, and a bias toward shipping and iteration.