AI Engineer

Fullstack AI Engineer

Required 3 days onsite

Location:

Charlotte, NC - local candidates

Glider:

Start:
May

• MUST PUT CURRENT AND INTENDED LOCATION ON RESUME
• MUST SUBMIT AT THE CORRECT RATE FOR THE LOCATION
• four candidates submittal per supplier. Additional spots will not be provided for rejected candidates

We are seeking a highly skilled Full‑Stack AI Engineer to design, develop, and deploy AI‑powered applications. The ideal candidate will have hands‑on experience integrating AI/ML models—particularly LLMs—into production systems, along with strong front‑end and back‑end engineering capabilities.

• Design, build, and maintain end‑to‑end AI-driven applications, including user interfaces, APIs, and data pipelines.
• Integrate large language models (OpenAI, Azure OpenAI, open‑source LLMs) into products or internal systems.
• Develop scalable backend services using technologies such as Python, Node.js, .NET, or Java.
• Build responsive and intuitive front‑end interfaces using React, Angular, or similar frameworks.
• Architect and implement vector databases, embeddings, and retrieval‑augmented generation (RAG).
• Implement prompt engineering, evaluation, and optimization of AI models.
• Collaborate with cross‑functional teams (product, data, cloud, architecture) to deliver production‑grade AI solutions.
• Own CI/CD pipelines, testing frameworks, and deployment processes (Azure, AWS, GCP).
• Ensure security, privacy, and compliance for AI systems handling sensitive data.

• 5+ years of experience in software engineering (full‑stack).
• Strong proficiency in front‑end technologies (React, Angular, Type Script).
• Strong backend development skills in Python, Node.js, .NET, or Java.
• Hands‑on experience integrating LLMs or ML models into applications.
• Experience with cloud‑native development (Azure preferred if relevant to your org).
• Proficiency with vector DBs (Pinecone, Chroma, Redis, Cosmos DB with vectors).
• Solid understanding of REST APIs, GraphQL, microservices, and event‑driven architecture.
• Knowledge of ML lifecycle tools (Lang Chain, Semantic Kernel, Prompt Flow, etc.).

• Experience with RAG systems, embeddings, and fine‑tuning LLMs.
• Experience with MLOps or AI Ops.
• Familiarity with enterprise‑grade security and governance around AI adoption.
• Prior experience building internal AI agents, copilots, or workflow automation systems.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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