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Gen AI Architect

E-Solutions

 

Charlotte, NC, USA

Posted On: 30+ days ago
Experience: 15+ years
Availability: Onsite
Openings: 1
Category: Gen AI Architect
Tenure: Contract - Corp-to-Corp
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Description

Responsibilities:

  • Define the organization’s GenAI architecture, strategy, and technical roadmap.
  • Design and oversee scalable solutions using LLMs, RAG, vector databases, AI agents, and multimodal AI.
  • Evaluate models, platforms, frameworks, and build-versus-buy options.
  • Establish standards for prompt engineering, model evaluation, orchestration, and LLMOps.
  • Design cloud-native AI platforms, APIs, data pipelines, and integration patterns.
  • Ensure solutions meet requirements for security, privacy, governance, performance, and cost.
  • Implement safeguards against hallucinations, prompt injection, data leakage, and unauthorized access.
  • Lead architecture reviews, proof-of-concepts, and production deployments.
  • Partner with product, data, engineering, security, and business stakeholders.
  • Mentor technical teams and communicate complex AI concepts to senior leaders.

Requirements:

  • Bachelor’s or master’s degree in computer science, AI, Data Science, Engineering, or a related field.
  • Experience in software architecture, engineering, machine learning, or data engineering.
  • Hands-on experience designing or delivering GenAI or LLM solutions.
  • Very strong knowledge of LLMs, embeddings, prompt engineering, RAG, vector search, and model evaluation.
  • Proficiency in Python, Java, JavaScript, TypeScript, or a similar language.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience with APIs, microservices, containers, Kubernetes, CI/CD, and distributed systems.
  • Understanding of AI security, data privacy, responsible AI, and governance.
  • Excellent communication, leadership, and problem-solving skills.
  • Experience with Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenAI, Anthropic, Gemini, or open-source models.
  • Familiarity with LangChain, LlamaIndex, Semantic Kernel, MLflow, Databricks, or similar tools.
  • Experience with AI agents, fine-tuning, knowledge graphs, or multimodal applications.
  • Cloud, AI, machine learning, or data engineering certifications

Education

Bachelor's or Master's degrees

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