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Generative Ai Developer Jobs in California (NOW HIRING)

Generative AI Engineer

Sunnyvale, CA · On-site

$100 - $150/hr

Generative AI Engineer - Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

As a software engineer, generative ai at WRITER, you'll be at the forefront of expanding human ... Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ...

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. Responsibilities : • ...

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand and interact with the physical world, with a focus on training and deploying ...

We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on ...

We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on ...

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Generative Ai Developer information

See California salary details

$18

$44

$99

How much do generative ai developer jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for generative ai developer in California is $44.70, according to ZipRecruiter salary data. Most workers in this role earn between $23.27 and $54.09 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What job categories do people searching Generative Ai Developer jobs in California look for?

The top searched job categories for Generative Ai Developer jobs in California are:

What cities in California are hiring for Generative Ai Developer jobs?

Cities in California with the most Generative Ai Developer job openings:

Infographic showing various Generative Ai Developer job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $92,966 per year, or $44.7 per hour.

Senior Generative AI Developer - Google Cloud

Jobtailor

Irvine, CA • On-site

$140 - $210/hr

Other

Posted 5 days ago


Job description

  • Design, build, test, and deploy Generative AI applications and intelligent agents on Google Cloud.
  • Develop single-agent and multi-agent solutions using Google Agent Development Kit.
  • Integrate Gemini models with enterprise APIs, databases, applications, and business workflows.
  • Deploy AI applications using Agent Engine, Cloud Run, GKE, or other appropriate GCP services.
  • Build Retrieval-Augmented Generation solutions using services such as BigQuery, Vertex AI Vector Search, Cloud Storage, and Document AI.
  • Develop APIs, microservices, agent tools, MCP integrations, and event-driven workflows.
  • Build data pipelines to ingest, transform, chunk, embed, index, and retrieve structured and unstructured data.
  • Implement session management, memory, tool calling, human approval, and agent orchestration patterns.
  • Apply automated testing, CI/CD, logging, monitoring, tracing, evaluation, and cost-management practices.
  • Implement Google Cloud security using IAM, service accounts, Workload Identity Federation, Secret Manager, and private networking.
  • Troubleshoot issues across agents, models, APIs, data pipelines, integrations, security, and cloud deployments.
  • Create architecture diagrams, technical designs, API specifications, deployment guides, and operational documentation.
  • Own technical workstreams and provide design reviews, code reviews, and guidance to other developers.
  • Participate in client discovery, architecture, testing, deployment, and knowledge-transfer activities.
Requirements
  • Significant experience developing and deploying applications on Google Cloud.
  • Advanced Python development experience.
  • Hands-on experience building Generative AI or agentic applications.
  • Experience with Google Agent Development Kit, including agents, tools, workflows, sessions, state, and multi-agent patterns.
  • Experience integrating Gemini models using Vertex AI or Google Gen AI SDKs.
  • Experience with Agent Engine, Cloud Run, GKE, Cloud Functions, or similar GCP runtimes.
  • Experience designing and implementing RAG solutions.
  • Experience with BigQuery and Google Cloud data services.
  • Experience building APIs using frameworks such as FastAPI.
  • Experience with REST APIs, asynchronous processing, event-driven architecture, and microservices.
  • Understanding of MCP and its use in connecting agents to enterprise tools and systems.
  • Experience with SQL, document stores, object storage, embeddings, semantic search, or vector databases.
  • Experience with Git, automated testing, CI/CD, Docker, and infrastructure as code.
  • Understanding of Google Cloud IAM, service accounts, Secret Manager, networking, logging, and monitoring.
  • Ability to evaluate tradeoffs involving model quality, latency, security, scalability, reliability, and cost.
Core Competencies

Demonstrates expertise in developing and deploying Generative AI applications on Google Cloud, utilizing advanced Python programming and integrating various Google Cloud services. Proficient in building APIs, data pipelines, and implementing security measures while ensuring high-quality, scalable, and reliable solutions.

Highest-signal resume keywords
  • Google Cloud Application Development
  • Advanced Python Development
  • Generative AI Application Building
  • API Development with FastAPI
  • Data Pipeline Construction
ATS Optimization Keywords Hard Skills
  • Python
  • Google Cloud
  • Generative AI
  • API Development
  • BigQuery
  • SQL
  • Microservices
  • CI/CD
  • Docker
  • Event-Driven Architecture
Industry Keywords
  • Generative AI
  • Agentic Applications
  • MCP
  • Asynchronous Processing
  • Retrieval-Augmented Generation
  • Data Services
  • Cloud Security
  • Monitoring
  • Logging
  • Orchestration Patterns
Tools & Technologies
  • Google Agent Development Kit
  • Agent Engine
  • Cloud Run
  • GKE
  • Vertex AI
  • Cloud Functions
  • Document AI
  • Secret Manager
  • Git
  • Infrastructure as Code
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