AI/ML Engineer, Internal Platforms - REMOTE

• Design, build, and improve AI agent capabilities using modern LLMs.

• Develop scalable backend services and RESTful APIs using Python.

• Build and optimize prompt workflows, retrieval-augmented generation (RAG), and AI agent orchestration.

• Experiment with emerging AI models, frameworks, and technologies.

• Evaluate model performance, reliability, and output quality.

• Collaborate with engineering and product teams to develop and deploy AI-powered features.

• Deploy, monitor, and maintain scalable AI systems in production environments.

• Improve the accuracy, efficiency, and reliability of AI applications.

• Stay current with advancements in generative AI, machine learning, and agent-based architectures.

Required Qualifications

• Strong software engineering experience with Python.

• Hands-on experience developing applications powered by large language models (LLMs).

• Experience integrating AI APIs and building intelligent applications.

• Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI agent frameworks.

• Experience developing backend APIs using FastAPI or comparable technologies.

• Experience with cloud infrastructure, preferably AWS, GCP, or Azure.

• Strong analytical, troubleshooting, and problem-solving skills.

• Excellent communication and cross-functional collaboration skills.

• Ability to work independently in a fast-paced, remote engineering environment.

Preferred Qualifications

• Experience deploying production-ready AI agents or generative AI products.

• Knowledge of retrieval-augmented generation (RAG), tool calling, prompt engineering, and model evaluation.

• Experience designing multi-step AI workflows and agent orchestration systems.

• Contributions to open-source AI projects or development of independent AI applications.

• Familiarity with monitoring, evaluating, and optimizing production AI systems.

• Experience working in AI-first technology organizations.

Work Arrangement: Remote

Employment Type: Full-time

Compensation: To be confirmed based on the applicable engagement structure.

Our client is committed to providing equal employment opportunities and evaluating qualified applicants based on their skills, experience, and professional qualifications.

The recruitment process may incorporate AI-assisted assessment tools to support candidate evaluation, with final hiring decisions made through human review.