Location: Burbank, CA (100% Onsite) Job Type: Full-Time Experience Level: Mid-Senior (10+ Years) Industry: Information Technology & Services Position Overview Carter Support Services is seeking a highly experienced Senior AI/ML Engineer to design, develop, and deploy advanced AI solutions. This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows . The ideal candidate will bring deep expertise in Python, cloud-based AI deployment (Azure), and modern NLP techniques , along with experience delivering production-grade AI systems. Key Responsibilities
Design and implement AI/ML solutions using Python and modern ML frameworks
Develop and optimize prompt engineering strategies for LLM-based systems
Build and deploy RAG (Retrieval-Augmented Generation) pipelines
Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications
Develop and orchestrate agentic AI workflows with tool/function calling
Implement vector search solutions using vector databases or MongoDB
Ensure CI/CD integration and cloud deployment (Azure preferred)
Establish observability, monitoring, and evaluation frameworks for AI systems
Collaborate cross-functionally to deliver production-ready AI features
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, or related field
10+ years of experience in software engineering or AI/ML roles
7+ years of Python experience (expert-level proficiency required)
7+ years of Microsoft Azure experience , including Azure Machine Learning
7+ years of DevOps experience , including CI/CD pipelines
7+ years of MongoDB or similar database experience
Strong experience with LLM integration and RAG architectures
Experience with prompt engineering and context optimization
Solid understanding of NLP and transformer-based models
Experience with vector databases and search systems
Familiarity with agentic AI workflows and tool/function calling
Preferred Qualifications
Experience with Azure OpenAI API
Experience building scalable, enterprise-grade AI applications
Background in AI system monitoring, evaluation, and optimization