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Entry Level Ai Data Engineer Jobs in California (NOW HIRING)

AI Data Engineer

Los Angeles, CA ยท On-site

$123K - $148K/yr

We are hiring an AI Data Engineer to own the seam between "customer says yes" and "data is flowing into Spiral." You will run technical discovery with new customers, design the integration that ...

AI Data Software Engineer

San Francisco, CA ยท On-site

$134K - $162K/yr

They are seeking an AI Data Software Engineer who will work closely with AI research labs to develop data production workflows and ensure the reliability of data pipelines. Responsibilities : โ€ข ...

Data Engineer - AI

Sunnyvale, CA ยท 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 ...

Data Engineer

Sunnyvale, CA ยท On-site

$150K - $450K/yr

Our mandate is to advance research, nurture the next generation of AI builders, and drive ... The Role As a Data Engineer specializing in Natural Language Processing (NLP) and large-scale data ...

Data Engineer

Sunnyvale, CA ยท On-site

$150K - $450K/yr

Our mandate is to advance research, nurture the next generation of AI builders, and drive ... The Role As a Data Engineer specializing in Natural Language Processing (NLP) and large-scale data ...

Data Engineer

Cupertino, CA ยท On-site

$141K - $169K/yr

The Data Engineering team within the MGC organization plays a critical role in supporting data ... We are leveraging Generative AI and Machine Learning technologies to provide best-in-class data ...

Data Engineer

Los Angeles, CA ยท On-site

$123K - $148K/yr

An opportunity to build autonomous surgical robotic systems driven by image guidance and AI ... The Data Engineer is responsible for designing, building, and maintaining the data pipelines that ...

AI ML Data Engineer

Sunnyvale, CA ยท On-site

$136K - $163K/yr

Hi, Title: AI ML Data Engineer Location : Sunnyvale, CA (3 days work from office) Need Local Candidates - In Person Interview Must Skills Needed: * Snowflake and Python/Scala/Java * SQL, No SQL ...

Data Engineer AI

Sunnyvale, CA ยท On-site

$105K - $110K/yr

Data Analyst / Engineer Who We Are: Quest Global delivers world-class end-to-end engineering ... Work experience - AI integration, Agentic AI * Secondary: Tableau What You Will Bring: * Create and ...

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Showing results 1-20

Entry Level Ai Data Engineer information

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior data scientists or AI research directors, which can offer compensation in that range including salary, bonuses, and stock options. Entry-level AI data engineering positions usually have lower salaries, but compensation can increase significantly with experience, skills, and responsibilities in the field.

What are the key skills and qualifications needed to thrive as an Entry Level AI Data Engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

What engineer makes 500,000 a year?

Highly experienced senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn salaries approaching or exceeding $500,000 annually, especially with bonuses and stock options. These roles typically require advanced skills, extensive experience, and often work in high-demand industries like technology or finance.

How can I become an AI engineer with no experience?

To become an entry-level AI data engineer with no experience, focus on building foundational skills in programming languages like Python, learn about data management and machine learning concepts, and complete online courses or certifications in AI and data engineering. Gaining hands-on experience through personal projects, internships, or contributing to open-source initiatives can also help demonstrate your abilities to employers.

What is an Entry Level AI Data Engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

Which 3 jobs will survive AI?

Entry Level AI Data Engineers are likely to continue being in demand as they develop and maintain AI models, requiring skills in data management, programming, and machine learning tools. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as data scientists, AI specialists, and cybersecurity analysts, are also expected to persist despite AI automation. These roles often require specialized knowledge and adaptability that AI cannot fully replicate yet.
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 job categories do people searching Entry Level Ai Data Engineer jobs in California look for? The top searched job categories for Entry Level Ai Data Engineer jobs in California are:
What cities in California are hiring for Entry Level Ai Data Engineer jobs? Cities in California with the most Entry Level Ai Data Engineer job openings:
Infographic showing various Entry Level Ai Data Engineer job openings in California as of July 2026, with employment types broken down into 68% Full Time, 22% Part Time, and 10% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.
AI Data Engineer

AI Data Engineer

UJET

Los Angeles, CA โ€ข On-site

$123K - $148K/yr

Other

Posted 4 days ago


Job description

Opportunity

UJET's conversation-analytics product, Spiral, is helping product, support, and CX leaders see what their customers are actually saying at scale. We ingest voice recordings, chat transcripts, surveys, and ticket data from every CCaaS, CRM, and storage system our customers can hand us, transcribe and PII-redact at scale, and use LLMs to surface user stories, taxonomies, and the trends that drive product and operational decisions.ย 

We are hiring an AI Data Engineer to own the seam between "customer says yes" and "data is flowing into Spiral." You will run technical discovery with new customers, design the integration that brings their data into our pipeline, and then build it end-to-end,ย  writing the code that adapts their data, wiring the cloud infrastructure that hosts the connection, and shipping the result into production. This is a hybrid role that combines pre-sale technical scoping with hands-on data-pipeline engineering. You will be the customer's technical counterpart from the first discovery call through steady-state ingest. You will be a member of the Spiral engineering team in every operational sense - working in a shared codebase, opening pull requests, participating in code review, debugging in production, and shipping changes through CI alongside the rest of engineering. This role is engineering-team membership with a customer-facing dimension; it is not a customer-success or pre-sales role that occasionally touches code.

Responsibilities

  • Run technical discovery with new customers to scope what data is available, where it lives, and how it will reach Spiral
  • Design the integration approach for each customer: whether that's cloud-to-cloud bucket access, vendor push uploads, scheduled API pulls, file drops, or auth-protected exports and explain the tradeoffs to their engineering counterpart
  • Shepherd credential and access exchange between the customer and Spiral - cloud access policies, OAuth or token-based authentication setup, key handoff - and stay on the thread until access is verified end-to-end
  • Write the code that adapts each customer's data shape into our ingestion contract, and ship it to production through code review
  • Make infrastructure-as-code changes to provision the cloud resources, identity grants, and secrets each new customer requires
  • Configure and operate the orchestration that runs each customer's recurring ingest; validate end-to-end through run history, logs, and metrics
  • Reconcile ingested data against source-system counts; diagnose and backfill historical gaps
  • Own customer relationships post-go-live: schema changes, new feed requests, data-format drift, and surfacing upsell opportunities back to the account team
  • Partner with Sales, Customer Success, and Spiral Engineering to compress time-to-first-data on every new deal

ย Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, Data Science, or Data Analytics with a CS/computing focus - or an equivalent rigorous technical degree
  • Prior production engineering experience with data pipelines, integrations, or analytics infrastructure - internship, contract, or full-time all qualify
  • Daily fluency with a standard engineering workflow: working in a shared codebase via git, authoring pull requests, giving and receiving substantive code review, debugging from logs, and shipping through CI - this is everyday work in this role, not a once-a-quarter activity
  • Comfort using AI as part of the everyday engineering workflow - LLM APIs, AI-assisted coding tools, prompt design, and a clear-eyed view of where AI multiplies the work and where its first pass needs to be overridden
  • Comfort writing production code in a modern typed or scripting language (years of experience scaling with level - new grads with strong fundamentals welcome)
  • Working knowledge of a major cloud provider - identity and access management, object storage, secrets handling, and the security model that governs cross-organization access
  • Experience with at least one data orchestration or ETL system, whether durable workflow, batch scheduler, or stream processor
  • Strong SQL chops; comfortable querying data to validate and reconcile what landed against what was sent
  • Customer-facing communication skills - able to hold a technical conversation with a customer's engineering counterpart and leave with a decision
  • Clear written communication, async-first, as most coordination happens over email, chat, and tickets across multiple timezones
  • A bias toward decisions over open questions, and a habit of writing the recommendation, not just the options

ย Stand-out Qualifications

  • Hands-on experience with Temporal or another durable workflow engine
  • OAuth integration experience (Salesforce JWT Bearer or Client Credentials especially)
  • Infrastructure-as-code experience with AWS CDK or Terraform
  • Experience with a columnar analytics database (ClickHouse, BigQuery, Snowflake, Redshift, DuckDB)
  • Background in contact center, CCaaS, or CX domains (UJET, Genesys, Five9, Twilio, Aircall, Talkdesk, NICE)
  • Comfort estimating cost and runtime of transcription or LLM pipelines at six-figure-file scale
  • Experience building with LLM APIs (Anthropic, OpenAI, AWS Bedrock, or equivalent) - evaluation, prompt design, cost and latency tradeoffs
  • Has used AI coding agents on a non-trivial engineering project and can articulate where the agent multiplied them and where they had to override its first pass
  • Prior experience as a Forward-Deployed Engineer, Solutions Engineer, Implementation Engineer, or Technical Account Manager

Annual US Hiring Range: $80,000 - $100,000

*A candidate's actual placement within this range will depend on geographic location, work experience, education, and/or skill level.
Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.

This is hybrid role with in-office collaboration required in Santa Monica, California.ย Applicants must currently reside in the Greater Los Angeles area to be considered; no relocation will be provided.ย 

#LI-Hybrid