AI Data Engineer Jobs in Washington
AI Data Engineer jobs in Washington are among the most active in the country, with strong demand across cloud computing, aerospace, healthcare informatics, and enterprise software from entry-level associates through principal engineers. Seattle and Redmond anchor most of the hiring, with a smaller but growing concentration in Bellevue, where Microsoft, Amazon, and Boeing have built deep data and AI teams. The most sought-after specialties in Washington listings are large-scale ML pipeline development, real-time data infrastructure, and Azure and AWS platform engineering. Find a role that fits below and apply directly.
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In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with distributed processing and large-scale data processing.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the job
The AI and Data Protection team builds and operates the high-throughput, high-availability content analysis services that power Google's AI and data protection capabilities. Our technology is fundamental to Cloud Sensitive Data Protection (Cloud SDP), Gmail and Google Drive's Data Loss Prevention (DLP) systems, Gemini training data protection, inference protection with Model Armor, and a wide range of other Google products.
We develop the infrastructure, APIs, algorithms, and models that provide fast, scalable classification and redaction of sensitive information and AI content risks.
As a Software Engineer, you will contribute to high-impact initiatives to create and enhance our classification models, improve the reliability, efficiency, and performance of our AI security and content analysis engines. You will innovate and deliver end-to-end solutions that safeguard data for Google, as well as Google Cloud customers.
You will provide technical guidance to other engineers, and work closely with partner teams, cross-functionally and with customers.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Develop server code in C++, Java or Go for content analysis with high availability at scale.
- Develop novel algorithms for detecting AI security risks, classifying structured and unstructured sensitive information.
- Train, evaluate, and productionize ML/Natural Language Processing (NLP) models for token tagging and payload classification tasks.
- Develop data mining pipelines, synthetic data generation pipelines, and build datasets for training and evaluation.
- Partner with research groups on developing innovative ML/NLP solutions.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with distributed processing and large-scale data processing.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the job
The AI and Data Protection team builds and operates the high-throughput, high-availability content analysis services that power Google's AI and data protection capabilities. Our technology is fundamental to Cloud Sensitive Data Protection (Cloud SDP), Gmail and Google Drive's Data Loss Prevention (DLP) systems, Gemini training data protection, inference protection with Model Armor, and a wide range of other Google products.
We develop the infrastructure, APIs, algorithms, and models that provide fast, scalable classification and redaction of sensitive information and AI content risks.
As a Software Engineer, you will contribute to high-impact initiatives to create and enhance our classification models, improve the reliability, efficiency, and performance of our AI security and content analysis engines. You will innovate and deliver end-to-end solutions that safeguard data for Google, as well as Google Cloud customers.
You will provide technical guidance to other engineers, and work closely with partner teams, cross-functionally and with customers.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Develop server code in C++, Java or Go for content analysis with high availability at scale.
- Develop novel algorithms for detecting AI security risks, classifying structured and unstructured sensitive information.
- Train, evaluate, and productionize ML/Natural Language Processing (NLP) models for token tagging and payload classification tasks.
- Develop data mining pipelines, synthetic data generation pipelines, and build datasets for training and evaluation.
- Partner with research groups on developing innovative ML/NLP solutions.
See All 51 AI Data Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI Data Engineer JobsAI Data Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI Data Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
- Amazon Web Services14
- Amazon11
- Meta3
- Microsoft3
- Google2
Top Industries Hiring
- Technology & Software
- Retail
- E-Commerce & Online Marketplaces
What Washington Employers Look For
The qualifications that appear most often in AI data engineer jobs across Washington.
- Bachelor's or master's degree in computer science, data engineering, or a closely related technical field
- Hands-on experience building and maintaining production data pipelines on Azure, AWS, or Google Cloud
- Proficiency in Python and SQL with demonstrated experience in Apache Spark or distributed compute frameworks
- Experience with MLOps practices, including model deployment, monitoring, and retraining workflows
- Familiarity with modern data orchestration tools such as Apache Airflow, dbt, or Databricks
- Strong communication skills for collaborating with data scientists, product managers, and engineering teams
AI Data Engineer Jobs in Washington: Frequently Asked Questions
How do you become a ai data engineer in Washington?
Washington does not require a state-issued license to work as an ai data engineer, so the path centers on education and demonstrated technical skill. Most Washington employers expect at least a bachelor's degree in computer science, data science, or a related field, with a master's degree valued at larger organizations like Microsoft and Amazon. Building a portfolio of end-to-end pipeline projects, contributing to open-source data tooling, and earning cloud certifications from AWS or Azure strengthens candidacy considerably in this market.
How much do AI data engineers make in Washington?
AI data engineers in Washington earn a median of about $163,350 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $79,930 for the lowest 10% to over $220,040 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai data engineers in Washington?
Employers hiring ai data engineers in Washington right now include Amazon Web Services, Amazon, and Meta, based on current listings on Migrate Mate as of September 2026. Washington's density of major tech headquarters and cloud platform teams makes it one of the deepest markets in the country for this role.
Which Washington cities have the most ai data engineer jobs?
Seattle, Redmond, and Bellevue have the most ai data engineer openings in Washington. Seattle and Redmond drive the bulk of demand thanks to the headquarters presence of Amazon, Microsoft, and a cluster of high-growth cloud and AI startups, while Bellevue's expanding enterprise and fintech sector has added a steady share of openings in recent years.
Are there remote ai data engineer jobs in Washington?
Yes, and more than most fields. About 40% of ai data engineer openings tied to Washington are remote or hybrid as of September 2026, reflecting how naturally the work fits a distributed environment. Pipeline development, data modeling, and MLOps work are the functions most commonly offered with full remote flexibility, while roles requiring close collaboration with on-site hardware or real-time infrastructure teams tend to require at least hybrid attendance.
How can I get hired as a ai data engineer in Washington with little or no experience?
The most realistic entry path is landing a data engineering associate or junior data analyst role at one of Washington's large tech employers and building toward ai data engineering from within. Amazon and Microsoft both run structured new-graduate programs that place candidates in data platform and AI infrastructure teams. Candidates without industry experience can strengthen their profile by completing an AWS or Azure data engineer certification, publishing end-to-end pipeline projects on GitHub, and targeting adjacent roles in data analytics or data operations that commonly transition into engineering tracks.
Where can I find and apply to ai data engineer jobs in Washington?
You can find and apply to ai data engineer jobs in Washington on Migrate Mate, which lists current Washington openings updated regularly. Search for roles that match your experience level and specialization, then apply directly to the ones that fit.
See All 51 AI Data Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
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