Gen AI Architect - Full Time - Onsite - Dallas, TX - Direct Client

Key Responsibilities Define the GenAI architecture strategy, ensuring alignment with enterprise technology standards, security frameworks, and governance principles. Design and oversee the implementation of LLM-based applications, integrating large-scale models such as GPT, Claude, Gemini, or custom fine-tuned models into enterprise systems. Partner with business and technology stakeholders to identify high-value AI use cases across automation, natural language processing, knowledge management, and data enrichment. Evaluate and guide the adoption of cloud-native AI services (Azure OpenAI, AWS Bedrock, Vertex AI, etc.) and vector database technologies (Pinecone, Chroma, Milvus, etc.). Lead AI model orchestration, retrieval-augmented generation (RAG) pipelines, and multi-agent workflows to create scalable and context-aware solutions. Establish best practices for prompt engineering, model evaluation, performance monitoring, and ethical AI standards. Collaborate with data engineering and DevOps teams to ensure MLOps readiness, including CI / CD for model deployment and versioning. Mentor cross-functional teams on AI design patterns and help drive AI literacy and innovation culture across the organization. Required Qualifications 10+ years of experience in software architecture, with at least 3+ years in AI / ML solution design or GenAI-focused implementations. Proven experience designing and deploying LLM-powered applications in enterprise environments. Strong knowledge of Python, REST APIs, vector search, embeddings, and orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel. Experience with cloud AI ecosystems (Azure OpenAI, AWS Bedrock, GCP Vertex AI). Understanding of data governance, privacy, and security principles related to AI workloads. Excellent communication and stakeholder management skills, with the ability to translate complex AI concepts into actionable business value. Preferred Skills Experience in retrieval-augmented generation (RAG), multi-agent design, or fine-tuning transformer models. Background in enterprise data architecture, analytics platforms, or cognitive automation. Prior experience working in real estate, financial services, or large-scale enterprise transformation programs is a plus. What You’ll Bring A passion for solving complex business challenges using Generative AI. Ability to bridge the gap between data science, engineering, and enterprise architecture. Leadership presence to influence executive and technical stakeholders alike.