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Ai Monitoring Jobs in California (NOW HIRING)

Integrate AI models developed by AI engineers into product backends while continuously improving scalability, monitoring, and resilience based on latency, error rates, and operational costs. * Domain ...

New

AI Engineer

San Francisco, CA · On-site

$150 - $210/hr

AI Engineer Location: San Francisco, CA, in-office Compensation: 150,000 - $210,000 Company ... Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate ...

New

Monitor and improve agents' performance via user simulations and evaluations. Requirements * 3+ years of experience in software development, AI engineering, or NLP in a production environment.

Develop high-performance front-end interfaces for AI agent control, monitoring, and visualization. * Build scalable backend services that support real-time AI interactions, knowledge retrieval, and ...

Applied AI Engineer

San Francisco, CA · On-site

$130 - $170/hr

Create evaluation frameworks to measure and improve AI performance across investment research, due diligence, and portfolio monitoring tasks * Design and implement systems that maintain traceability ...

New

Cloud AI Ops / AI Monitoring; and, Cloud Discovery. Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range ...

Monitoring & Observability * System Metrics: Define and track key ML system metrics, including ... AI-Specific Metrics & Drift: Define and monitor critical ML system KPIs, including model latency ...

AI Software Engineer

El Segundo, CA · On-site

$80K - $210K/yr

We build AI systems that determine how logistics decisions are made - not just how they're executed ... Own high model reliability and uptime by implementing monitoring across your work. * Data ...

Senior AI Infrastructure Engineer

Santa Clara, CA · On-site

$127K - $173K/yr

Monitoring & Observability * System Metrics: Define and track key ML system metrics, including ... AI-Specific Metrics & Drift: Define and monitor critical ML system KPIs, including model latency ...

Cloud AI Ops / AI Monitoring; and, Cloud Discovery. Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range ...

Cloud AI Ops / AI Monitoring; and, Cloud Discovery. Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range ...

Resolve AI is solving this by building a transformative, truly autonomous AI Production Engineer ... Drive adoption through data-driven interventions: monitor usage, sentiment, and feedback signals.

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI ... model improvement and monitoring in production. Team Collaboration & Delivery Excellence

AI Solutions Manager, West

San Francisco, CA · On-site +1

$140K - $175K/yr

As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That's where we come in. Arize AI is the leading AI & Agent Engineering ...

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI ... model improvement and monitoring in production. Team Collaboration & Delivery Excellence

Staff AI Engineer

Menlo Park, CA · On-site

$190 - $270/hr

... modern DevOps practices (Terraform, CI/CD, monitoring). * Excellent communication ... If you're an AI engineer who thrives at the intersection of cutting‑edge research and ...

AI Operations Lead

San Francisco, CA · On-site

$150K - $190K/yr

You'll build the evaluation frameworks and monitoring that tell us whether an AI workflow is actually working - not just whether it's live. Find the leverage: You'll partner cross-functionally to ...

Showing results 41-60

Ai Monitoring information

What is AI monitoring?

AI monitoring refers to the process of continuously observing and analyzing artificial intelligence systems to ensure they operate as intended. This includes tracking performance, detecting anomalies, ensuring compliance with ethical guidelines, and identifying potential biases or errors. Effective AI monitoring helps organizations maintain transparency, improve system reliability, and ensure that AI models make fair and accurate decisions. It is essential in applications where AI impacts critical business or societal outcomes.

What are some common challenges faced by professionals in AI monitoring roles, and how can they be addressed?

Professionals in AI Monitoring often encounter challenges such as managing large volumes of data, identifying and responding to atypical model behavior, and ensuring compliance with ethical and regulatory standards. Staying updated on the latest AI trends and best practices, utilizing robust monitoring tools, and collaborating closely with data scientists and engineers can help address these challenges. Regular training and open communication within cross-functional teams are also essential to maintain effective oversight and quickly mitigate potential issues.

What are the key skills and qualifications needed to thrive as an AI monitoring specialist, and why are they important?

To thrive as an AI Monitoring Specialist, you need a solid understanding of data analysis, machine learning concepts, and system monitoring, often supported by a degree in computer science or a related field. Familiarity with monitoring platforms like Datadog, Prometheus, or Splunk, as well as experience with scripting languages and AI model management tools, is typically required. Attention to detail, critical thinking, and strong communication skills help specialists identify issues quickly and collaborate with technical teams. These skills and qualities are crucial for ensuring AI systems operate reliably, securely, and efficiently in real-world applications.

What is the difference between Ai Monitoring vs Data Analyst?

AspectAi MonitoringData Analyst
Required CredentialsTypically requires knowledge of AI systems, programming, and data analysis toolsRequires statistical, analytical, and data visualization skills, often with a degree in data science or related fields
Work EnvironmentOften involves monitoring AI systems in real-time, using specialized software, in tech or AI-focused companiesAnalyzes data sets, creates reports, and provides insights, working in various industries like finance, marketing, or healthcare
Employer & Industry UsageCommon in AI development firms, tech companies, and organizations deploying AI solutionsWidely used across industries for decision-making, reporting, and strategic planning

While both roles involve working with data, Ai Monitoring focuses on overseeing AI system performance and ensuring operational accuracy, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

Infographic showing various Ai Monitoring job openings in California as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 8% Part Time, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

[America Tech] AI SW Engineer

Nota AI

Sunnyvale, CA • On-site

$120 - $190/hr

Other

Posted 3 days ago

New


Job description

The Nota America Product Team is dedicated to expanding Nota's presence in the U.S. market. Leveraging Nota's AI expertise, we identify customer challenges and build domain-specific AI capabilities into real-world products and services.

In this role, you will design backend systems and model-serving architectures that power AI services, building secure and scalable service foundations that include authentication, authorization, access control, APIs, and data layers. You will integrate AI models developed by AI engineers into production systems while designing and advancing Agent-based services alongside the team. Our focus is on delivering reliable, production-ready AI capabilities that create real customer value.

What You’ll Do at This Position

In this role, you will experience the full lifecycle of applying AI technologies across diverse industries and scaling them into global services. You will transform domain-specific AI capabilities into commercial products while designing, building, and evolving backend systems and Agent services based on product requirements and the team's technical direction.

From problem definition and system architecture to implementation, deployment, operations, and continuous improvement, you will play a key role throughout the entire product development lifecycle.

  • Design and develop the core backend architecture for AI products, including authentication and authorization, access control, APIs, data models, and asynchronous processing. Build efficient integration architectures that balance AI model cost, latency, and availability.
  • Model Serving API Development & Production Integration
  • Develop and operate model-serving APIs across cloud and on-premise environments to support reliable AI services. Integrate AI models developed by AI engineers into product backends while continuously improving scalability, monitoring, and resilience based on latency, error rates, and operational costs.
  • Domain-Specific AI Service Development & Commercialization
  • Collaborate with AI engineers to integrate AI models and external AI/LLM APIs into production backend services. Rapidly validate ideas and evolve them into production-ready services equipped with APIs, data infrastructure, authentication, authorization, and monitoring.
  • Agent Service Design & Development
  • Design and implement Agent services by understanding execution flows and tool-calling mechanisms. Build robust Agent architectures that include tool interfaces, state management, permission control, and error and failure handling.
  • AI Tool Interface & Integration Layer Development
  • Provide APIs and tool interfaces that allow Agents to reliably invoke AI capabilities. Design input validation, permission control, timeout strategies, and error-handling mechanisms to ensure dependable integrations.
  • Design, develop, and commercialize backend architectures for AI products.
  • Design, build, and operate core backend capabilities for AI and Agent services, including authentication, authorization, access control, APIs, data models, and asynchronous processing.
  • Define service reliability metrics (SLI/SLO) for AI and Agent services and build resilient architectures with timeout, fallback, retry, circuit breaker, and monitoring mechanisms.
  • Rapidly prototype and validate services using AI development tools.
  • Develop model-serving APIs and integrate AI models into production backend systems.
  • Implement service logic that integrates LLMs and multimodal APIs while optimizing response quality, cost, and latency.
  • Design and develop Agent execution flows, state management, tool integrations, and error-handling mechanisms.
  • Define and implement APIs and tool interfaces that expose AI capabilities to Agent services.
  • Collaborate with Product, Business, and AI Engineering teams to analyze customer problems and design AI-powered solutions.
  • 3+ years of experience designing, developing, deploying, and operating backend services.
  • Strong foundation in computer science fundamentals, including operating systems, computer architecture, data structures, and algorithms.
  • Proficiency in Python, Java, or both, with hands-on experience building and operating production backend services.
  • Experience designing API architectures, shared middleware, authentication and authorization, input validation, and testing frameworks using backend frameworks such as FastAPI, Flask, Django, or Spring Boot.
  • Experience designing schemas, managing transactions, and optimizing indexes and queries in relational databases such as PostgreSQL or MySQL.
  • Ability to quickly understand complex requirements and lead technical design, implementation, deployment, and operations.
  • Strong commitment to code quality, automated testing, performance, and reliability, with experience using logs and metrics to identify and resolve production issues.
  • Excellent communication skills with the ability to translate business requirements into technical solutions.
  • Experience rapidly prototyping and validating services using AI development tools to improve engineering productivity.
  • Experience deploying and operating LLM- or AI model-based services in production, including hands-on design and implementation of Agent services.
  • No restrictions on overseas travel.
Pluses
  • Experience designing streaming responses and asynchronous API architectures.
  • Experience designing reusable backend frameworks or leading service architecture across multiple products.
  • Experience designing and operating B2B SaaS backend systems, including multi-tenancy and organization/role-based access control.
  • Experience designing and operating asynchronous architectures using caching, message queues, or background job processing.
  • Experience building SLI/SLO-driven service operations and monitoring systems.
  • Experience optimizing backend performance in high-traffic production environments.
  • Mobile application development experience, or a strong interest in mobile development with a willingness to learn new technology stacks as needed.
  • Experience optimizing model-serving APIs for performance and cost while scaling services to support increasing traffic.
  • Experience productionizing LLMs, VLMs, or multimodal AI models.
  • Experience building and operating production Agent services for real users.
  • Experience implementing workflows using Agent orchestration frameworks such as LangGraph or MCP servers.
  • Ability to bridge user experience and business requirements with technical solutions.
  • (Additional assignments may be included during the process.)
A Message from the Team

Our team embraces a collaborative and flexible culture where everyone works closely together to turn ideas into products quickly. Rather than focusing solely on research, we are passionate about building products that solve real customer problems and can be validated in the market.

One of our greatest strengths is our ability to adapt rapidly evolving AI technologies to specific industry domains and engineer production-ready services with scalability, performance, and cost efficiency in mind. We continuously balance experimentation with commercialization, creating an environment where both technology and products evolve together.

Please Check Before Applying!
  • This job posting is open continuously, and it may close early upon completion of the hiring process.
  • Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
  • Providing false information in the submitted materials may result in the cancellation of the application.
  • Please be aware that references will be checked before finalizing the hiring decision.
  • Compensation will be discussed separately upon successful completion of the final interview.
  • There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
  • To support the employment of persons with disabilities, you may optionally submit a copy of your disability registration certificate under "Additional Documents," if administrative verification is required. Submission is optional and does not affect the evaluation process.
  • Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
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