AI Architect - Irving

Photon•Irving, TX

8d•$62,000 - $217,000•Onsite

About The Position

We are looking for an experienced AI Architect to design and lead the architecture of enterprise-grade AI, Generative AI, and Machine Learning solutions. The ideal candidate will have strong expertise in AI/ML architecture, LLMs, cloud platforms, data engineering, MLOps, and enterprise application integration. The AI Architect will work closely with business, engineering, data science, and technology teams to translate business requirements into scalable, secure, reliable, and cost-effective AI solutions.

Requirements

Strong experience in AI/ML architecture and enterprise solution architecture.
Strong understanding of Generative AI and LLM technologies.
Hands-on experience with: LLMs and foundation models, RAG, Prompt engineering, Embeddings and vector databases, AI agents / agentic workflows, Model evaluation and guardrails, Fine-tuning / PEFT, NLP and/or Computer Vision
Programming experience in Python and preferably Java/TypeScript.
Strong knowledge of REST APIs, microservices, event-driven architecture, and distributed systems.
Experience with cloud platforms such as AWS / Azure / GCP.
Experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or equivalent.
Experience with vector databases such as Pinecone, Weaviate, Milvus, pgvector, or Azure AI Search.
Knowledge of Docker, Kubernetes, CI/CD, MLOps/LLMOps, and infrastructure automation.
Strong understanding of data platforms, databases, data pipelines, and data governance.
Knowledge of AI security concepts including prompt injection, data leakage, model security, access control, and responsible AI.

Responsibilities

Define end-to-end AI/ML and Generative AI architecture for enterprise solutions.
Design scalable architectures covering LLMs, RAG, AI agents, NLP, computer vision, predictive analytics, and ML platforms.
Evaluate and select appropriate LLMs, foundation models, embedding models, vector databases, AI frameworks, and cloud AI services.
Design RAG pipelines, including document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
Architect Agentic AI solutions, including tool calling, workflow orchestration, memory, planning, and multi-agent patterns.
Establish enterprise standards for AI governance, security, privacy, responsible AI, model evaluation, and observability.
Design MLOps/LLMOps pipelines for model development, deployment, monitoring, versioning, evaluation, and continuous improvement.
Integrate AI capabilities with enterprise systems, APIs, databases, data platforms, and existing applications.
Work with cloud platforms such as AWS, Azure, or Google Cloud to build production-grade AI platforms.
Provide technical leadership to AI/ML engineers, data scientists, software engineers, and DevOps teams.
Conduct architecture reviews, proof-of-concepts, technology evaluations, and technical feasibility assessments.
Optimize AI solutions for performance, scalability, latency, reliability, and cost.
Define architecture documentation, technical standards, reference architectures, and reusable AI components.
Stay current with emerging developments in Generative AI, LLMs, multimodal AI, agentic AI, and AI infrastructure.