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Ai Manager Jobs in Riverside, CA (NOW HIRING)

Staff AI Engineer

Irvine, CA · On-site

$200K - $230K/yr

Description Emergence AI is building next-generation agentic AI systems that move beyond code ... Own the workflow execution engine, state management, error handling, versioning, and sharing ...

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Ai Manager information

See Riverside, CA salary details

$24.2K

$104.1K

$196.3K

How much do ai manager jobs pay per year?

As of Jun 11, 2026, the average yearly pay for ai manager in Riverside, CA is $104,120.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,502.00 and $143,801.00 per year, depending on experience, location, and employer.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position such as an AI executive, chief AI officer, or senior AI researcher with extensive experience and expertise. These roles often involve strategic leadership, advanced technical skills, and managing large AI projects or teams, and they usually require advanced degrees and industry certifications.

What is the role of an AI manager?

An AI manager oversees the development, implementation, and maintenance of artificial intelligence projects within an organization. They coordinate teams of data scientists and engineers, ensure project goals align with business objectives, and often require knowledge of machine learning tools and programming languages. Their role involves strategic planning, resource management, and ensuring ethical AI practices.

What does an AI Manager do?

An AI Manager oversees the development, implementation, and optimization of artificial intelligence solutions within an organization. They lead AI teams, manage projects, and ensure alignment with business goals while addressing technical and ethical concerns. AI Managers collaborate with data scientists, engineers, and executives to drive innovation and improve operational efficiency. They also stay updated on industry trends and advancements to leverage AI effectively.

What are the key skills and qualifications needed to thrive in the Ai Manager position, and why are they important?

To thrive as an AI Manager, you need a strong background in computer science, machine learning, project management, and proven experience leading AI initiatives, often supported by a relevant degree or industry certifications. Familiarity with AI frameworks and tools such as TensorFlow, PyTorch, cloud platforms, and knowledge of data governance and MLOps is commonly required. Excellent leadership, problem-solving, and communication skills help AI Managers effectively coordinate cross-functional teams and translate business objectives into actionable AI solutions. These competencies are essential for successfully driving AI projects from conception to deployment while aligning with organizational goals.

How much does an AI manager make?

An AI manager's salary typically ranges from $100,000 to $180,000 annually, depending on experience, location, and industry. Senior AI managers with specialized skills in machine learning and data analysis may earn higher compensation, often supplemented with bonuses and stock options.

Which 5 jobs will survive AI?

AI managers oversee the development and deployment of artificial intelligence systems, a role that requires strategic thinking, domain expertise, and understanding of AI tools. Jobs that involve complex problem-solving, creativity, emotional intelligence, and human interaction—such as healthcare professionals, educators, skilled trades, creative artists, and mental health practitioners—are less likely to be fully replaced by AI. These roles often require nuanced judgment and empathy that AI cannot replicate fully.

What types of teams or departments does an AI Manager typically collaborate with?

AI Managers work closely with data scientists, software engineers, product managers, and business stakeholders to ensure AI projects align with company objectives. They often coordinate with IT teams for infrastructure requirements, as well as legal and compliance teams regarding data privacy and ethical AI practices. Close collaboration with these groups helps deliver robust and scalable AI solutions, fostering a multidisciplinary approach that enhances project success. By acting as a bridge between technical and non-technical teams, AI Managers ensure that business needs are clearly understood and translated into effective AI strategies.

What are the most commonly searched types of Ai jobs in Riverside, CA? The most popular types of Ai jobs in Riverside, CA are:
What job categories do people searching Ai Manager jobs in Riverside, CA look for? The top searched job categories for Ai Manager jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Ai Manager jobs? Cities near Riverside, CA with the most Ai Manager job openings:
Infographic showing various Ai Manager job openings in Riverside, CA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $104,120 per year, or $50.1 per hour.

Staff AI Engineer

Emergence AI

Irvine, CA • On-site

$200K - $230K/yr

Other

Medical, Dental, Vision, Retirement

Posted 19 days ago


Job description

Description

Emergence AI is building next-generation agentic AI systems that move beyond code generation to provable task completion, verification, and long-horizon autonomy. Our Platform focuses on automating complex, mission-critical data workflows, from ingestion and transformation through analysis, decisioning, and action.


We work with customers in semiconductors, life sciences, and other data-intensive industries to turn fragmented, high-stakes data into trustworthy, continuously-operating AI Agents.  

Requirements

As a Staff AI Engineer at Emergence, You Will:


Bring AI expertise, product intuition, and a builder's mindset to advance the frontier of what agents can accomplish for our customers. You will work across applied research and engineering to solve many open problems in AI, including:

  • Designing AI agent workflows and orchestration systems for our platform and solutions
  • Designing optimal data representations and modes of interaction between agents and their environments
  • Building verification and safety systems that enable autonomous agent execution in high-stakes enterprise environments

Representative Projects:


Workflow Orchestration & Custom Agent Builder. Build the platform that lets customers define their own investigation workflows  from natural language to production-grade multi-step agents. Own the workflow execution engine, state management, error handling, versioning, and sharing capabilities that make custom workflows reliable and reusable.


Verification & Policy Engine. Design and implement the verification system that makes autonomous agent execution safe , policy-as-code frameworks, constraint checking, audit trails, and proof artifacts in an Enterprise systems. Enable agents to move to autonomous direction when verified safe.


Agent Operations & Observability. Build the provenance tracking, drill-down capabilities, and debugging tools that make agent behavior transparent and debuggable from query execution traces to multi-agent coordination visibility. Make non-deterministic AI systems observable and trustworthy.


Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Emergence measure and improve AI quality systematically , eval harnesses, ground truth management, regression detection, A/B testing for agents.


Context Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Emergence agent workflows depend on managing what agents see, remember, and pass between steps.


Responsibilities:

  • Drive cutting-edge AI capabilities across multiple layers of the agent platform  from workflow orchestration and verification systems to custom workflow builders and agent operations infrastructure.
  • Ensure a high craft and quality bar in both AI agent performance and platform reliability , build systems that are fast, correct, and maintainable.
  • Collaborate with fellow engineers, designers, product managers, and customers to integrate platform functionality into frontier agentic products and deliver customer value.
  • Contribute to platform reliability, code quality, AI evaluation, testing, and maintenance across the broader engineering team.
  • Mentor and elevate engineers around you , share knowledge, review code thoughtfully, and raise the technical bar for the team.

Required Qualifications:

  • 8+ years of experience building backend systems, distributed systems, or data infrastructure, with at least 2+ years focused on AI/ML engineering in production environments.
  • Experience building and shipping multi-model or multi-provider AI systems in production using LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, function calling, or agent frameworks at scale.
  • Track record at both startups AND enterprise companies , you know how to move fast while maintaining reliability and can navigate both worlds effectively.
  • Familiarity with context management, session state, or memory systems in AI or distributed systems. You've thought about what the model sees and why it matters.
  • Experience with evaluation frameworks, testing strategies for AI systems, or quality measurement in production ML systems.
  • Strong systems thinking around safety, verification, and correctness , you've built guardrails, validation layers, or compliance systems where "probably right" isn't good enough.
  • Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.
  • A bias toward full ownership: you navigate ambiguity well, don't wait for perfect specs, and take problems from concept through production deployment.
  • Comfortable working with a small, fast-moving team where you'll dive in, take ownership, mentor others, and elevate the engineering culture.

Compensation Range: $200,000 to $230,000 USD


Emergence Benefits:

  • Comprehensive health & wellness benefits, including medical, dental, vision, HSA, and FSA options
  • Voluntary insurance offerings for additional coverage
  • 401(k) plan with company match
  • Flexible time off and company holidays to support rest and recharge
  • Flexible remote work environment
  • One-time home office setup stipend
  • Ongoing monthly stipend to support your work-from-home needs