About the Company
Our client is developing intelligent software designed to go beyond generating responses and deliver dependable AI experiences that understand context, take action, and complete meaningful tasks. The team focuses on turning advances in AI models into reliable, production-ready systems that provide practical value to users.
Blue Signal, an award-winning executive search firm, is supporting the search for this opportunity. The firm specializes in executive recruitment across multiple industries and professional services.
About the Role The AI Engineer will work across machine learning, software engineering, infrastructure, and product development to build and deploy reliable AI-powered applications. The focus is on turning model capabilities into systems that perform consistently in real-world environments.
You will develop large language model (LLM) applications and agent-based workflows, manage model integration and deployment, and improve system performance through practical evaluation and continuous iteration. The role involves taking ownership from initial technical exploration through production delivery, monitoring, and ongoing improvement.
This opportunity is suited to an engineer who can work across the full AI stack, write production-quality code, troubleshoot complex issues, and make sound technical decisions in a rapidly evolving environment. The team values practical engineering ability, ownership, collaboration, and measurable results.
Key Responsibilities
•Build and deploy production AI capabilities that connect model intelligence with dependable user experiences.
•Develop LLM-powered systems involving prompt engineering, tool use, contextual memory, agent workflows, and multi-step execution.
•Translate probabilistic model outputs into structured, consistent, and reliable application behavior.
•Manage solutions across model integration, infrastructure, deployment, monitoring, and product delivery.
•Diagnose and resolve issues involving model behavior, orchestration, infrastructure, application logic, and user experience.
•Improve AI systems across output quality, latency, cost, scalability, and production reliability.
•Develop practical evaluation methods and use real-world feedback and performance signals to guide improvements.
•Collaborate with product and engineering teams to turn ambiguous challenges into scalable, production-ready solutions.
•Take ownership of technical exploration, implementation, deployment, and continuous improvement.
Required Qualifications and Skills
•Strong foundation in machine learning, neural networks, and modern model architectures.
•Hands-on experience training, fine-tuning, integrating, serving, or deploying machine learning models.
•Strong software engineering skills, including the ability to write clean, maintainable, production-quality code.
•Applied experience building LLM systems involving prompts, tools, memory, agents, inference, and evaluation.
•Ability to work across machine learning models, infrastructure, and product development rather than focusing exclusively on modeling or research.
•Strong proficiency in Python.
•Familiarity with machine learning frameworks such as PyTorch, JAX, or comparable technologies.
•Strong problem-solving and debugging skills, particularly in ambiguous and rapidly changing technical environments.
•Demonstrated engineering judgment, end-to-end ownership, and the ability to take on increasing technical responsibility.
•A practical approach to shipping solutions, learning from results, and iterating to improve performance.
What This Opportunity Offers
•Fully remote work available to candidates throughout the United States.
•High-impact projects spanning machine learning, AI systems, infrastructure, and product development.
•End-to-end ownership from technical exploration through production deployment and ongoing improvement.
•The opportunity to build practical LLM and agent-based systems using modern AI engineering technologies.
•A fast-moving, collaborative environment that values technical quality, sound engineering judgment, and demonstrated impact over pedigree.
Work Arrangement
This is a nationwide remote opportunity open to candidates based in the United States. The role offers the chance to contribute across the AI engineering lifecycle, from model integration and system architecture through deployment, monitoring, and product improvement.