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Entry Level Generative Ai Prompt Engineer Jobs in California

As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in ...

As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in ...

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 : • ...

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 ...

As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in ...

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 ...

... generative AI. The Product Engineer, AI will be responsible for owning critical products ... actions • Run prompt tuning, tool usage evaluations, and comparative model benchmarks • ...

... generative AI ecosystem and apply them pragmatically. • Communicate clearly with technical and ... advanced prompt engineering strategies, evaluation frameworks, and RAG pipelines • Conducting ...

Lead and conduct advanced research in AI and Generative AI to develop innovative solutions ... AWS Bedrock, Azure Open AI Service, Prompt Engineering & RAG, Vector Databases and Embedding

Showing results 41-60

Entry Level Generative Ai Prompt Engineer information

What are some common challenges faced by entry level generative AI prompt engineers, and how can they overcome them?

Entry-level generative AI prompt engineers often encounter challenges such as crafting effective prompts that yield reliable outputs, staying current with rapidly evolving AI models, and interpreting ambiguous model responses. Overcoming these challenges requires continuous learning, experimentation, and collaboration with more experienced engineers or data scientists. Participating in team discussions, reviewing prompt libraries, and regularly testing prompts with different models can help newcomers build their expertise and confidence in the role.

What is an entry level generative AI prompt engineer?

Entry Level Generative AI Prompt Engineers are professionals who design, test, and refine prompts to interact with generative AI models, such as those used in chatbots or content creation tools. Their role involves understanding how AI responds to different inputs, troubleshooting issues, and optimizing prompts for accuracy and relevance. They typically collaborate with developers, data scientists, and content teams to improve AI outputs for various applications. This entry-level position is ideal for those with basic programming knowledge, strong communication skills, and an interest in artificial intelligence.

What are the key skills and qualifications needed to thrive as an entry level generative AI prompt engineer?

To thrive as an Entry Level Generative AI Prompt Engineer, you need a foundational understanding of natural language processing, basic programming skills (often in Python), and familiarity with AI concepts, typically supported by a relevant degree or coursework. Experience with AI platforms like OpenAI, Hugging Face, or Google Cloud AI, as well as prompt design tools, is commonly required. Creativity, analytical thinking, and strong written communication help you craft effective prompts and collaborate with cross-functional teams. These skills are crucial for developing high-quality AI outputs and ensuring solutions align with user needs and project goals.

What is the difference between Entry Level Generative Ai Prompt Engineer vs Entry Level Data Scientist?

AspectEntry Level Generative Ai Prompt EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, AI, or related; basic understanding of AI modelsBachelor's in CS, Statistics, or related; knowledge of data analysis
Work EnvironmentAI labs, tech companies, startupsData analysis teams, research institutions, tech firms
Industry UsageAI development, NLP, chatbot creationData analysis, predictive modeling, research

While both roles require a foundational understanding of technology and data, Entry Level Generative Ai Prompt Engineers focus on designing prompts for AI models, especially in NLP, whereas Entry Level Data Scientists analyze data to derive insights. The roles overlap in technical skills but differ in application and focus areas.

What are the most commonly searched types of Generative Ai Prompt Engineer jobs in California? The most popular types of Generative Ai Prompt Engineer jobs in California are:
What job categories do people searching Entry Level Generative Ai Prompt Engineer jobs in California look for? The top searched job categories for Entry Level Generative Ai Prompt Engineer jobs in California are:
What cities in California are hiring for Entry Level Generative Ai Prompt Engineer jobs? Cities in California with the most Entry Level Generative Ai Prompt Engineer job openings:
Infographic showing various Entry Level Generative Ai Prompt Engineer job openings in California as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Test Engineer-AI/LLM

OPPO US Research Center

Palo Alto, CA • On-site

Full-time

Re-posted 13 days ago


Job description

OPPO US Research Center is seeking a full-time meticulous and innovative AI/LLM Test Engineer to join our cutting-edge AI team. In this critical role, you will evaluate the performance, reliability, and safety of Large Language Models (LLMs) in real-world product scenarios and test end-to-end generative AI solutions. Your work will directly shape how users experience AI-powered features by ensuring robustness, accuracy, and alignment with product goals. This is a unique opportunity to pioneer testing methodologies for next-generation AI systems at the forefront of technology.
We are also seeking a Contractor based LLM Evaluation & QA Engineer to support the testing and validation of large language model (LLM)-powered applications. You will help implement test strategies, execute evaluation workflows, and assist in model performance validation across diverse generative AI use cases.
This contract role is ideal for someone with hands-on experience in AI/ML evaluation, QA engineering, or data analysis who wants to deepen their exposure to generative AI systems.
Requirements
Full-time position requirement:
Core Testing & Evaluation
  • Design and execute performance tests for LLMs across diverse product use cases (e.g., chatbots, content generation etc.).
  • Develop automated test frameworks to evaluate LLM outputs for accuracy, bias, safety, and coherence.
  • Conduct end-to-end testing of integrated generative AI solutions, including APIs, data pipelines, and user interfaces.

Optimization & Validation
  • Collaborate with ML engineers to validate fine-tuned models and optimize prompts for target scenarios.
  • Analyze model failures, edge cases, and adversarial inputs to identify risks and improvement areas.
  • Benchmark LLM performance against industry standards and product-specific KPIs.

Collaboration & Quality Assurance
  • Partner with product, engineering, and research teams to define test requirements and acceptance criteria.
  • Document defects, performance metrics, and test results to drive data-driven improvements.
  • Advocate for AI ethics and safety through rigorous testing of fairness, bias mitigation, and content moderation.

Innovation & Tooling
  • Build scalable tools for synthetic test data generation, prompt variation testing, and automated evaluation workflows.
  • Stay current with advancements in generative AI testing, including red-teaming techniques and evaluation frameworks (e.g., HELM, Dynabench).
  • Propose novel testing strategies for emerging challenges (e.g., hallucinations, context drift).

Basic Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.
  • 1+ years of experience in software testing, data science, or ML validation, with exposure to AI/ML systems.
  • Proficiency in Python and testing frameworks (e.g., PyTest, Selenium).
  • Hands-on experience evaluating LLMs in production environments (e.g., GPT, Claude, Llama, Gemini).
  • Strong analytical skills for dissecting model behavior, statistical performance, and failure modes.
  • Familiarity with cloud platforms (GCP, Azure, or AWS) and MLOps tooling (e.g., MLflow, Weights & Biases).
  • Experience with version control (Git) and agile development methodologies.

Preferred Qualifications:
  • Master's degree in AI, Machine Learning, or a related field.
  • Expertise in prompt engineering, LLM fine-tuning (e.g., LoRA, RLHF), or optimization techniques.
  • Experience with automated evaluation tools (e.g., LangChain, TruLens) or LLM-specific test suites.
  • Knowledge of data pipelines, SQL/NoSQL databases, and API testing (e.g., Postman).
  • Background in statistics, quantitative analysis, or data visualization for test insights.
  • Contributions to AI safety/ethics initiatives or open-source LLM evaluation projects.
  • Experience testing mobile-integrated AI solutions (Android/iOS).

Contractor position requirements:
Testing & Evaluation Support:
  • Execute pre-defined performance tests for LLMs across various tasks (e.g., summarization, Q&A, chatbot flows).
  • Run scripted evaluations to assess outputs for factuality, coherence, and safety.
  • Perform manual and automated test execution on APIs and LLM-integrated user interfaces.

Prompt & model validation:
  • Assist ML engineers in evaluating prompt variations and prompt-tuning outcomes.
  • Log and analyze failure cases, anomalies, and edge cases based on provided guidelines.

Collabration & Documentation
  • Work with QA leads, product managers, and ML engineers to understand test goals and criteria.
  • Report defects, compile evaluation summaries, and maintain testing logs.

Tooling & Antomation:
  • Use existing internal tools or frameworks to automate test runs and result collection.
  • Contribute to prompt generation, input templating, or result tagging processes.

Basic Qualifications:
  • Bachelor's degree or equivalent work experience in a technical field (e.g., Computer Science, Engineering, Data Science).
  • 6+ months experience in software QA, data labeling, LLM evaluation, or ML testing projects.
  • Basic Python proficiency, especially for data processing and automation tasks.
  • Familiarity with LLMs (e.g., GPT, Claude, Gemini) and prompt-based outputs.
  • Comfortable working with tools like Jupyter, Postman, or testing dashboards.
  • Detail-oriented with good documentation habits.

Contractor Details:
  • Duration: Long term
  • Rate: Commensurate with experience
  • Conversion Opportunity: High-performing contractors may be considered for full-time roles

Benefits
OPPO is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
The US base salary range for this full-time position is $100,000-$200,000 + bonus + long term incentives benefits. Our salary ranges are determined by role, level, and location.