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Ai Data Engineer Jobs in California (NOW HIRING)

Kai Cyber, Inc.

Senior Data Engineer, AI Platform

San Jose, CA · On-site

$124K - $168K/yr

About the Role We are looking for a Senior Data Engineer (AI Platform) to design and build scalable data systems that power next-generation AI and Generative AI applications. This is a senior, hands ...

ITbility

Data Engineer - AI

Sunnyvale, CA · On-site

$136K - $163K/yr

* Data Engineer - AI * Sunnyvale, California * Contract - 6 + Months We are looking for a hands-on Data Engineer - AI for Sunnyvale, California to join a team focused on strengthening.. Please email me ...

Deloitte

Databricks Data Engineering Manager

Sacramento, CA · On-site

$122K - $146K/yr

Work you'll do As a Lead Data Engineer II in our AI & Data practice, you will leverage your extensive real-world experience to lead the delivery of transformative data and AI programs for our clients ...

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All JobsAi Data Engineer JobsAi Data Engineer Jobs in California

Ai Data Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do ai data engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for ai data engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What does an AI data engineer do?

An AI Data Engineer designs, builds, and manages data pipelines and infrastructure to support AI and machine learning models. They collect, process, and store large datasets, ensuring data is clean, structured, and accessible for AI applications. Their role involves working with big data tools, cloud platforms, and databases to optimize performance and scalability. Collaboration with data scientists and software engineers is essential to deploy and maintain AI solutions efficiently.

What are the key skills and qualifications needed to thrive as an AI data engineer?

To thrive as an AI Data Engineer, you need strong proficiency in programming (Python, SQL), data architecture, and machine learning fundamentals, typically supported by a degree in computer science, engineering, or a related field. Experience with big data tools (Spark, Hadoop), cloud platforms (AWS, Azure, GCP), and certifications like Google Professional Data Engineer are highly valuable. Excellent problem-solving skills, attention to detail, and effective team communication help distinguish top performers in this role. These abilities ensure the development of robust data pipelines and systems that power accurate AI solutions in a collaborative and rapidly-evolving environment.

What are some common challenges an AI data engineer might face in their daily work?

AI Data Engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality and consistency, and building scalable data pipelines to handle large volumes of information. Working closely with data scientists and software engineers requires strong collaboration and flexibility to adapt to shifting project requirements or algorithms changes. Keeping up with the latest developments in big data and machine learning tech stacks is also crucial. Overcoming these challenges provides a dynamic work environment and offers valuable learning and career growth opportunities.

What are the most commonly searched types of Ai Data Engineer jobs in California?

The most popular types of Ai Data Engineer jobs in California are:

What are popular job titles related to Ai Data Engineer jobs in California?

For Ai Data Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Ai Data Engineer jobs in California look for?

The top searched job categories for Ai Data Engineer jobs in California are:

What cities in California are hiring for Ai Data Engineer jobs?

Cities in California with the most Ai Data Engineer job openings:

Ai Data Engineer jobs near you
Infographic showing various Ai Data Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

Senior Data Engineer, AI Platform

Kai Cyber, Inc.

San Jose, CA • On-site

$124K - $168K/yr

Full-time

Re-posted 3 days ago

Job description

Kai is the AI company rebuilding cybersecurity for the machine-speed era. Founded by second time founders and trusted by Fortune 500 enterprises, Kai is building a future where security has no categories, no silos, and no human speed bottlenecks. The Kai Agentic AI Platform replaces fragmented, human-limited workflows with agentic AI systems that continuously contextualize, assess, reason, and execute security work at machine speed - making human defenders, superhuman.
Why Join Kai
  • Well-funded: With $125M raised, we have the capital, runway, and resolve to rebuild cybersecurity from first principles.
  • Proven: We've earned the trust of Fortune 500 and Global 1000 companies, and we're just getting started. Their confidence in Kai reflects what we've built: an AI-powered cybersecurity platform that performs at the scale and speed the enterprise demands.
  • Experienced founders: Our founding team consists of second-time entrepreneurs, each with over 20 years of experience in the cybersecurity industry. Their proven expertise and vision drive our ambitious goals.
  • World-class leadership team: Our Heads of AI, Engineering, and Product bring extensive experience from some of the world's most influential companies, ensuring top-tier mentorship, direction, and vision.
  • Frontier AI Applied Research Team: Our researchers operate at the leading edge of agentic AI systems, translating breakthrough capabilities into real-world cybersecurity applications.
  • Generous compensation: We offer highly competitive salaries, equity options, and a supportive work environment. Your contributions will be valued and rewarded as we grow together.

About the Role
We are looking for a Senior Data Engineer (AI Platform) to design and build scalable data systems that power next-generation AI and Generative AI applications.
This is a senior, hands-on technical role for someone who can operate across both classical data engineering and modern AI data infrastructure - including large-scale data pipelines, vector databases, and retrieval systems for LLM-powered applications.
You will work at the intersection of data engineering, AI infrastructure, and LLM systems, enabling high-quality data flow, retrieval, and storage for production-grade intelligence systems.
Key Responsibilities
  • Design and build scalable data pipelines for batch and real-time processing
  • Develop and maintain data infrastructure supporting AI/ML and Generative AI systems
  • Build and optimize retrieval pipelines for RAG and LLM-based applications
  • Design and manage vector data pipelines (embedding generation, indexing, storage, retrieval)
  • Implement hybrid retrieval systems (BM25 + vector search)
  • Work closely with AI/ML teams to enable training, evaluation, and inference workflows
  • Develop data models and storage systems optimized for large-scale AI applications
  • Ensure data quality, consistency, and reliability across pipelines
  • Optimize systems for performance, latency, scalability, and cost
  • Collaborate with product, engineering, and AI teams to translate requirements into data solutions

Required Qualifications
  • 4+ years of experience in Data Engineering or related fields
  • Strong experience building large-scale distributed data pipelines
  • Proficiency in Python and SQL; experience with Spark or similar frameworks
  • Experience with both batch and streaming systems (e.g., Kafka, Flink, Spark Streaming)
  • Experience working with cloud data platforms (AWS, GCP, Azure)
  • Solid understanding of data modeling, storage systems, and distributed systems
  • Experience supporting AI/ML workloads through data infrastructure
  • Strong ownership mindset and ability to operate in fast-paced environments

Preferred Qualifications
  • Experience working with LLM-powered systems and RAG pipelines
  • Familiarity with vector databases and ANN search systems
  • Experience in data systems for AI platforms or ML infrastructure
  • Background in search, recommendation systems, or information retrieval

Core Technical Expertise
Data Engineering & Pipelines
  • Batch and streaming pipelines (Spark, Flink, Kafka)
  • ETL/ELT design, data modeling, and data warehousing
  • Data quality, validation, and observability

AI Data Infrastructure
  • Data pipelines for ML training and inference
  • Feature stores and dataset versioning
  • Data preparation for LLM and GenAI systems

Vector Databases & Retrieval Systems
  • Milvus, Pinecone, Databricks Vector Search, FAISS
  • ANN algorithms (HNSW, IVF, PQ)
  • Hybrid retrieval (BM25 + vector search)
  • Embedding pipelines (text, code, image)

RAG & LLM Data Systems
  • Retrieval pipelines for LLM applications
  • Context construction and ranking
  • Data indexing and chunking strategies

Storage & Distributed Systems
  • Data lakes (S3, GCS, ADLS), Parquet, Delta Lake, Iceberg
  • Distributed systems design and scalability
  • Caching and low-latency data access

Platforms & Infrastructure
  • AWS, GCP, Azure
  • Databricks, BigQuery, Snowflake
  • Kubernetes, Ray (nice to have)

Performance & Optimization
  • Query optimization and indexing strategies
  • Cost optimization for large-scale data systems
  • Latency optimization for real-time retrieval

Apply