AI Architect

KAYGEN•Irvine, CA

About The Position

We are seeking an experienced AI Architect to lead the design, development, and deployment of scalable AI/ML solutions. This role requires a blend of deep technical expertise and leadership capability to architect enterprise-grade AI systems, guide cross-functional teams, and ensure alignment with business objectives.

Requirements

Strong expertise in ML algorithms and deep learning frameworks such as TensorFlow and PyTorch.
Solid foundation in statistics, data modeling, data analysis, and visualization techniques.
Proficiency in Python, R, and/or Java, with experience using AI/ML libraries and toolkits.
Hands-on experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, including their AI/ML services.
Experience with distributed data processing tools like Apache Hadoop, Apache Spark, and Apache Kafka.
Strong leadership and mentoring abilities
Excellent communication and stakeholder management skills
Strategic thinking and problem-solving mindset
Ability to work in a fast-paced, cross-functional environment.

Nice To Haves

Experience designing AI solutions in enterprise environments
Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management
Strong understanding of data governance and security best practices
Prior experience in stakeholder-facing or consulting roles

Responsibilities

Design end-to-end AI/ML architectures, including data pipelines, model training frameworks, deployment strategies, and system integration.
Assess and recommend appropriate tools, platforms, and frameworks based on scalability, performance, cost, and enterprise compatibility.
Lead and oversee the development, training, validation, and optimization of machine learning and deep learning models to meet business KPIs.
Ensure seamless integration of AI solutions with existing enterprise systems, applications, and databases.
Lead, mentor, and develop a team of data scientists, ML engineers, and AI specialists to drive innovation and delivery excellence.
Manage AI initiatives end-to-end, ensuring delivery within scope, timeline, and budget.
Translate complex AI concepts into business-friendly insights for stakeholders, ensuring alignment and informed decision-making.
Ensure AI systems comply with regulatory requirements and ethical standards, including data privacy, fairness, and bias mitigation.