Senior AI/ML Engineer

Job Title: Senior AI/ML Engineer

Location: Charlotte, North Carolina (On-site 4 days, 1 day remote)

Structure: 6 12-month Contract-to-Hire (W2 Only. We cannot work 1099 or C2C)

Work Authorization: We are unable to offer sponsorship

Summary:

Join the growing Service, Experience, and technology team in Charlotte, North Carolina. This role is primarily on-site, offering the opportunity to work hands-on with cutting-edge AI/ML technologies in a collaborative and impactful environment.

We re looking for a Senior AI Engineer who can:

• Lead AI/ML projects independently and collaborate across teams
• Mentor junior engineers and contribute to team growth
• Design and deploy scalable ML pipelines and LLM-based system

Responsibilities:

• Lead end-to-end delivery of AI/ML and LLM-based solutions from prototype to production
• Design, deploy, and maintain LLM-based systems in production environments
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines and vector-based search solutions
• Perform LLM prompt engineering, fine-tuning, and evaluation to improve model performance and relevance
• Monitor and evaluate LLM system performance and safety using tools like LangSmith or similar
• Build, deploy, and scale APIs and ML services using CI/CD pipelines
• Work within containerized and cloud environments (Kubernetes, AWS/Google Cloud Platform/Azure) for deployment and orchestration
• Collaborate cross-functionally to integrate machine learning capabilities into broader business systems
• Guide and mentor junior engineers in best practices across the AI/ML lifecycle

Requirements:

• Advanced proficiency in Python, Machine Learning, NLP, and text data analysis
• Demonstrated experience with:
  • Building and deploying LLM-based systems to production
  • LLM prompt engineering, fine-tuning, and evaluation techniques
  • Designing and implementing RAG architectures
  • Vector databases, embedding models, and semantic search
  • Monitoring and evaluation tools for LLMs (e.g., LangSmith)
• Strong understanding of MLOps practices including:
  • CI/CD pipelines for ML workflows
  • Model versioning and model registry management
  • Automated deployment and monitoring tools
• Familiarity with LLM deployment libraries such as LiteLLM, LLM Guardrails, or similar
• Experience with or willingness to learn Kubernetes and cloud platforms (AWS, Google Cloud Platform, Azure)

Eligibility:

• Applicants must be authorized to work in the U.S. on a permanent basis.
• Visa sponsorship is not available

Brooksource provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.