AI/Gen Architect

Hi,

Position : AI/Gen Architect

Location : Sunnyvale, CA

Duration : Long Term

An AI/Gen Architect is responsible for designing, building, and implementing scalable, secure, and ethical generative AI solutions by translating business needs into technical strategies. Key duties include leading cross-functional teams, selecting appropriate AI frameworks and cloud platforms, ensuring the end-to-end AI/ML lifecycle is managed, and collaborating with stakeholders to align AI initiatives with business objectives.

Key responsibilities

Strategic planning: Define and execute an AI architecture strategy, aligning it with business goals and key performance indicators.

Solution design: Architect and implement scalable AI/ML solutions, including data pipelines, storage, and processing frameworks, using cloud environments like AWS, Google Cloud, or Azure.

End-to-end lifecycle management: Oversee the entire AI/ML model lifecycle, from development and deployment to monitoring, optimization, and maintenance.

Technical leadership: Lead and mentor cross-functional teams, including data scientists, engineers, and other stakeholders, to ensure successful project outcomes.

Collaboration: Work closely with business leaders and other teams to integrate AI capabilities into products and services and ensure solutions meet business requirements.

Technology selection: Evaluate and choose the right AI frameworks, tools, and technologies, such as TensorFlow, PyTorch, and various large language models, for specific projects.

Compliance and ethics: Ensure AI solutions adhere to ethical standards, industry regulations, and best practices for governance, performance, and security.

Innovation: Stay up-to-date with the latest advancements in AI, machine learning, and data science to drive continuous innovation and improvement.

Required qualifications and skills

Education: Typically requires a Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

Experience: Proven experience in developing and deploying AI/ML solutions, with a minimum of 3-5 years often required in solution architecture roles.

Technical skills:

Deep understanding of machine learning, deep learning, NLP, computer vision, and statistical methods.

Proficiency with machine learning frameworks like TensorFlow and PyTorch.

Experience with cloud platforms (AWS, Google Cloud, Azure).

Expertise in MLOps for model validation, monitoring, and management.

Soft skills:

Strong problem-solving abilities and attention to detail.

Excellent communication, collaboration, and leadership skills.