Cloud AI/ML Architecture

Cloud Hybrid Technologies, LLC; San Jose (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

A technology solutions provider in California seeks a Cloud Architect to lead the design and optimization of cloud-based data architecture and oversee AI/ML workflows. This role requires strong expertise in data engineering and the implementation of CI/CD practices in cloud environments. Candidates should possess experience with Kubernetes and various cloud services, aiming to drive scalability and innovation within the company.

Qualifications

• Strong background in data engineering.
• Hands-on experience building cloud data solutions.
• Proficient in designing and optimizing cloud architectures.

Responsibilities

• Design and optimize cloud-based data architecture.
• Oversee all stages of AI/ML pipeline development.
• Implement automated deployment pipelines for ML models.
• Monitor infrastructure and AI workloads for optimization.

Skills

Data engineering

Cloud data solutions

AI/ML system design

Kubernetes

Automation and CI/CD

Tools

Cloud services

AI/ML platforms

Job description

• The Cloud Architect will be a key contributor to designing, evolving, and optimizing our company's cloud-based data architecture. This role requires a strong background in data engineering, hands-on experience building cloud data solutions, and a talent for communicating complex designs through clear diagrams and documentation. Must work EST hours.
• Strategy, Planning, and Roadmap Development: Align AI and ML system design with broader business objectives, shaping technology roadmaps and architectural standards for end-to-end cloud-driven analytics and AI adoption.
• Designing End-to-End AI/ML Workflows: Architect and oversee all stages of AI/ML pipeline development—data ingestion, preprocessing, model training, validation, deployment, monitoring, and lifecycle management within cloud environments.
• Selecting Technologies and Services: Evaluate and choose optimal cloud services, AI/ML platforms, infrastructure components (compute, storage, orchestration), frameworks, and tools that fit operational, financial, and security requirements.
• Infrastructure Scalability and Optimization: Design and scale distributed cloud solutions capable of supporting real-time and batch processing workloads for AI/ML, leveraging technologies like Kubernetes, managed ML platforms, and hybrid/multi-cloud strategies for optimal performance.
• MLOps, Automation, and CI/CD Integration: Implement automated build, test, and deployment pipelines for machine learning models, facilitating continuous delivery, rapid prototyping, and agile transformation for data and AI-driven products.
• Security, Compliance, and Governance: Establish robust protocols for data access, privacy, encryption, and regulatory compliance (e.g., GDPR, ethical AI), coordinating with security experts to continuously assess risks and enforce governance.
• Business and Technical Collaboration: Serve as the liaison between business stakeholders, development teams, and data scientists, translating company needs into technical solutions, and driving alignment and innovation across departments.
• Performance Evaluation & System Monitoring: Monitor infrastructure and AI workloads, optimize resource allocation, troubleshoot bottlenecks, and fine-tune models and platforms for reliability and cost-efficiency at scale.
• Documentation and Best Practices: Create and maintain architectural diagrams, policy documentation, and knowledge bases for AI/ML and cloud infrastructure, fostering a culture of transparency, learning, and continuous improvement.
• Continuous Innovation: Stay abreast of new technologies, frameworks, trends in AI, ML, and cloud computing, evaluate emerging approaches, and lead strategic pilots or proofs-of-concept for next-generation solutions.
• This role blends leadership in technology and systems architecture with hands-on expertise in cloud infrastructure, artificial intelligence, and machine learning, pivotal for driving innovation, scalability, and resilience in a modern enterprise.

Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract