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Live In Ai Validation Jobs in Riverside, CA (NOW HIRING)

D. in Computer Science, Artificial Intelligence, Software Engineering, or a closely related ... validating complex agent behaviors. • Deep understanding of security architecture principles as ...

In this role, you will be a primary technical authority responsible for designing the foundational ... validate design choices and mitigate technical risks. * Provide expert technical guidance and ...

... validating, and optimizing advanced AI ECG-based algorithms for Masimo's non-invasive medical device platforms. This role provides technical leadership in the design and deployment of robust, real ...

Sr Engineer, AI (ECG)

Irvine, CA · On-site

$140K - $170K/yr

... validating, and optimizing advanced AI ECG-based algorithms for Masimo's non-invasive medical device platforms. This role provides technical leadership in the design and deployment of robust, real ...

Power Systems AI/ML Engineer

Irvine, CA · On-site

$87K - $125K/yr

... validation, and ensure accuracy and reliability of AI outputs. * Optimize computational performance and ensure scalability of AI-driven functionalities across ETAP product suites. * Participate in ...

Power Systems AI/ML Engineer

Irvine, CA · On-site

$87K - $125K/yr

... validation, and ensure accuracy and reliability of AI outputs. * Optimize computational performance and ensure scalability of AI-driven functionalities across ETAP product suites. * Participate in ...

SDET, Remote opportunity

Irvine, CA · On-site +1

$130K - $145K/yr

Hybrid if local to Irvine, CA. 100% remote if you live more than 30 miles from the office. Our client is one of the leading mortgage technology companies in the country, investing heavily in AI ...

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Live In Ai Validation information

See Riverside, CA salary details

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How much do live in ai validation jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for live in ai validation in Riverside, CA is $54.25, according to ZipRecruiter salary data. Most workers in this role earn between $41.11 and $65.96 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Live In AI Validation Specialist, and why are they important?

To thrive as a Live In AI Validation Specialist, you need a solid background in computer science, data analysis, and machine learning concepts, often supported by a relevant degree or equivalent experience. Familiarity with tools such as Python, TensorFlow, and data annotation platforms, as well as an understanding of AI validation protocols, is typically required. Attention to detail, critical thinking, and strong communication skills are essential soft skills for ensuring accurate validation and effective collaboration with development teams. These competencies are crucial for maintaining AI system quality, reliability, and alignment with real-world requirements.

What are some common challenges faced by professionals in Live-In AI Validation roles, and how can they be addressed?

Professionals in Live-In AI Validation often encounter challenges such as managing large-scale data collection in real-time environments and ensuring the accuracy of AI outputs in dynamic, real-world settings. Collaboration with data scientists, engineers, and end users is key to troubleshooting unexpected behaviors and improving system reliability. Strong communication and adaptability help team members quickly respond to new scenarios or hardware changes during validation. Staying up-to-date with the latest AI validation tools and continuous feedback loops can also significantly enhance the effectiveness of the validation process.

What are Live In AI Validation jobs?

Live In AI Validation jobs involve working closely with artificial intelligence systems to test, review, and improve their performance in real-world settings. Professionals in this role typically monitor the outputs of AI algorithms, validate data quality, and provide feedback to ensure the AI operates accurately and ethically. These jobs may require living on-site or being embedded in environments where the AI is deployed, such as smart homes, research labs, or automated facilities. The goal is to bridge the gap between AI development and real-world application, ensuring the technology is reliable and effective.

What is the difference between Live In Ai Validation vs Live In Data Entry?

AspectLive In Ai ValidationLive In Data Entry
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, client-facing, flexible hoursRemote, client-facing, flexible hours
Industry UsageAI, tech, data servicesVarious industries, administrative tasks
Common Search IntentAI validation, data verification jobsData entry, administrative jobs

Live In Ai Validation involves verifying and validating AI-generated data to ensure accuracy, often requiring critical thinking and familiarity with AI tools. In contrast, Live In Data Entry focuses on inputting data into systems, emphasizing speed and accuracy. Both roles are remote and require similar skills but serve different functions within the data management industry.

What are the most commonly searched types of Ai Validation jobs in Riverside, CA? The most popular types of Ai Validation jobs in Riverside, CA are:
What are popular job titles related to Live In Ai Validation jobs in Riverside, CA? For Live In Ai Validation jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Live In Ai Validation jobs in Riverside, CA look for? The top searched job categories for Live In Ai Validation jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Live In Ai Validation jobs? Cities near Riverside, CA with the most Live In Ai Validation job openings:
Agentic AI Architect

Agentic AI Architect

Ingram Micro

Irvine, CA • On-site

Full-time

Re-posted 14 days ago


Ingram Micro rating

7.1

Company rating: 7.1 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

204th of 365 rated retail wholesalers


Job description

Job Summary:
Ingram Micro is a leading technology company for the global information technology ecosystem, and they are seeking a highly experienced and innovative Agentic AI Architect to join their AI CoE. The role involves designing foundational architecture for next-generation AI agent ecosystems, providing technical guidance, and mentoring engineers while ensuring compliance with architectural best practices.
Responsibilities:
• Lead the definition and design of the end-to-end reference architecture for enterprise-grade agentic AI systems, encompassing agent lifecycle management, interaction protocols, knowledge integration, and action execution frameworks.
• Develop detailed architectural blueprints, patterns, and standards for building, deploying, and integrating AI agents across diverse business domains and existing enterprise platforms (ERP, CRM, SCM, WMS).
• Design core components of the agentic ecosystem, including reasoning engines (leveraging LLMs), planning modules, perception interfaces, memory systems, and tool/API integration layers.
• Ensure architectural designs meet critical non-functional requirements, including scalability, reliability, security, maintainability, and cost-effectiveness.
• Drive the technical evaluation and selection of appropriate frameworks (e.g., Gogole ADK, LangChain, AutoGen, CrewAI), platforms, and tools for our agentic AI stack.
• Serve as a senior technical expert and thought leader on agentic AI architecture, multi-agent systems, LLM-driven autonomy, and related technologies.
• Lead the development of advanced prototypes and proof-of-concepts for core architectural components and novel agentic capabilities to validate design choices and mitigate technical risks.
• Provide expert technical guidance and architectural oversight to development teams working on specific AI agent projects.
• Collaborate with the Agentic AI Lead and other stakeholders to align architectural decisions with the overall AI strategy and roadmap.
• Establish and promote engineering best practices, coding standards, and design patterns for agentic AI development within the CoE.
• Contribute to the development of Agentic AI Tech Ops/MLOps/LLMOps strategies specifically tailored for the lifecycle management of AI agents.
• Ensure that architectural designs and implementations adhere to ethical AI principles (fairness, transparency, accountability, privacy) and relevant compliance requirements.
• Create and maintain comprehensive architectural documentation.
• Mentor and coach AI engineers and developers on advanced architectural concepts, design principles, and new technologies in the agentic AI space.
• Foster a culture of technical excellence, innovation, and knowledge sharing.
• Act as an internal evangelist for sound architectural practices in AI development.
• Work closely with data scientists, data engineers, security architects, infrastructure teams, and business stakeholders to ensure holistic and well-integrated agentic solutions.
• Translate complex business requirements and domain-specific challenges into effective and scalable architectural designs.
• Clearly articulate and defend architectural decisions to both technical and non-technical audiences.
Qualifications:
Required:
• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Software Engineering, or a closely related technical field.
• 10+ years of experience in software engineering and AI/ML system development, with at least 5-7 years focused on architecting and designing complex, distributed AI systems.
• Deep, hands-on expertise in architecting and implementing Agentic AI systems or autonomous intelligent agents. This includes practical experience with designing architectures for systems utilizing agentic frameworks and libraries (e.g., LangChain, AutoGen, CrewAI, LlamaIndex, Microsoft Semantic Kernel, Google's agentic stack including Vertex AI Search and Conversation, Agent Builder, or similar).
• Architecting solutions that leverage Large Language Models (LLMs) for core agent functionalities like reasoning, planning, and complex interaction (e.g., GPT series, Claude, Gemini, Llama models), including strategies for prompt management, context handling, RAG, and robust function calling.
• Strong proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).
• Expert understanding of software architecture principles, design patterns (e.g., microservices, event-driven architecture, SOA), APIs, and distributed systems engineering, with a proven ability to apply them to AI/agentic systems.
• Solid experience with MLOps/LLMOps practices and tools for model/agent lifecycle management, and a clear vision for how these apply to agentic AI.
• Significant experience with data architecture, data engineering, data pipelines, vector databases, and knowledge graphs as they pertain to enabling intelligent agents.
• In-depth knowledge of cloud computing platforms (e.g., GCP, AWS, Azure) and experience designing AI solutions on these platforms.
• Proven ability to lead the architectural design of complex technical projects and make critical technology choices.
• Exceptional analytical, problem-solving, and system-thinking skills.
• Strong communication and collaboration skills, with the ability to influence and guide technical teams.
Preferred:
• Demonstrated experience architecting agentic AI solutions for sales automation, customer service, or vendor management, supply chain management, logistics or inventory optimization ideally within the IT distribution or a similar complex B2B industry.
• Expertise in multi-agent systems (MAS) architecture, inter-agent communication protocols, and coordination strategies.
• Experience architecting systems incorporating reinforcement learning (RL).
• Familiarity with designing and implementing simulation environments for testing and validating complex agent behaviors.
• Deep understanding of security architecture principles as applied to AI and autonomous systems.
• Track record of defining and driving the adoption of new architectural standards or technology platforms within an organization.
• Experience contributing to or leading technical governance bodies (e.g., Architecture Review Boards).
Company:
Ingram Micro is a provider of technology products and supply chain management services. Founded in 1979, the company is headquartered in Irvine, USA, with a team of 10001+ employees. The company is currently Late Stage.

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