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AI Solution Architect

Techno-Comp, Inc.Raleigh, NC🇺🇸United States

Why this role stands out

This role offers an exceptional opportunity to shape the future of enterprise-grade AI while enjoying the flexibility of a hybrid work environment at a leading company. You will thrive here if you are a forward-thinking architect passionate about leveraging Generative AI and LLMs to drive meaningful technical impact. Apply today to accelerate your career and lead innovation within a high-performing team.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationRaleigh, NC, United States
DockerMicroservicesAWSGoogle CloudHugging FaceJavaPyTorchPythonTensorFlowGenerative AIRESTAzureKubernetesMachine LearningPrompt EngineeringCI/CDLangChainRAG

Job description

Job Title: AI Solution Architect

Location: Raleigh, NC (Hybrid)

Duration: Long Term Contract

Job Summary: We are looking for an experienced AI Solution Architect to design and implement scalable, secure, and enterprise-grade AI solutions. The ideal candidate will have strong experience in Generative AI, LLMs, cloud platforms, machine learning, data architecture, and AI application development, along with the ability to translate business requirements into technical solutions.

Required Skills:

· 8+ years of experience in software/solution architecture, with strong experience in AI/ML solutions.

· Hands-on experience with Generative AI and Large Language Models (LLMs).

· Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and AI agents.

· Experience with one or more cloud platforms: Azure, AWS, or Google Cloud Platform.

· Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent platforms.

· Strong programming experience in Python and/or Java.

· Experience with AI/ML frameworks such as LangChain, LlamaIndex, Hugging Face, PyTorch, or TensorFlow.

· Experience with vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, or Milvus.

· Strong understanding of REST APIs, microservices, event-driven architecture, and distributed systems.

· Experience with Docker, Kubernetes, CI/CD, and cloud-native architectures.

· Knowledge of AI security, responsible AI, data privacy, and model governance.

· Excellent communication, architecture documentation, and stakeholder-management skills.

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