Generative AI Architect

Generative AI Architect

Location : San Jose CA (Onsite)

Contract

We are seeking a highly skilled and visionary Generative AI Architect to lead the design, development, and deployment of advanced GenAI solutions. This role requires deep expertise in machine learning, large language models (LLMs), and cloud-native architecture, along with a strong understanding of enterprise needs and ethical AI considerations. The ideal candidate will drive innovation across the organization by aligning GenAI technologies with strategic business objectives.

Key Responsibilities:

Architecture & Design:

Design scalable, secure, and performant architectures for GenAI systems including LLMs, diffusion models, and multi-modal AI.

Define solution blueprints integrating GenAI into enterprise platforms, workflows, and data ecosystems.

Model Integration & Customization:

Evaluate, fine-tune, and integrate foundation models (e.g., OpenAI, Anthropic, open-source LLMs) for specific business use cases.

Build and manage pipelines for model training, prompt engineering, retrieval-augmented generation (RAG), and continuous learning.

Platform Development:

Collaborate with engineering teams to build GenAI platforms and APIs that support internal and external applications.

Ensure systems are designed for scalability, resilience, observability, and compliance.

Governance & Risk Management:

Establish AI governance frameworks, ensuring responsible AI usage aligned with regulatory, ethical, and privacy standards.

Implement controls for bias detection, explainability, and model monitoring.

Collaboration & Strategy:

Partner with product, data, security, and infrastructure teams to deliver GenAI capabilities across lines of business.

Provide thought leadership and evangelize GenAI strategy to stakeholders and executives.

Required Qualifications:

Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or related field.

8 years of experience in AI/ML architecture, with at least 2 years focused on GenAI or LLM-based systems.

Deep understanding of transformer models, tokenization, embeddings, and generative pipelines.

Hands-on experience with frameworks such as Hugging Face, LangChain, PyTorch, TensorFlow, or similar.

Proficient in cloud platforms (AWS, Azure, or Google Cloud Platform), containerization (Docker, Kubernetes), and CI/CD pipelines.

Familiarity with data privacy, intellectual property, and compliance issues surrounding AI.

Preferred Qualifications:

Experience with enterprise-scale AI/ML platforms or MLOps pipelines.

Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG frameworks.

Strong understanding of prompt engineering, few-shot learning, and human-in-the-loop systems.

Industry certifications in AI architecture or cloud architecture are a plus.

Soft Skills:

Strong communication and stakeholder management skills.

Strategic thinking with the ability to bridge technical execution and business outcomes.

Passion for innovation and continuous learning in the evolving field of generative AI.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.