Staff Engineer, Data Platform

San Diego, California

Live, first seen by us 67 days ago

Pay: USD 200,000–300,000/year — pay source
Salary 200,000 – 300,000 USD per year #LI-DM2
Read the full posting
Work setting: On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting
Employment: Full-time — employment source
Employment type Full Time Employee
Employment type in the employer’s posting: Full Time Employee
From the employer’s posting

What you’ll work on

Full posting

You will design and implement data APIs, dataset versioning, search and metadata systems that remain useful as datasets grow and schemas change.
Build dataset discovery, catalog and retrieval services, including LanceDB integration for indexing and search.
Create APIs that let developers pin an exact dataset version and retrieve only the data they are authorized to access.

From the employer’s posting

Reproducing a model’s results starts with knowing exactly which data it used. Shield AI’s AI Factory gives machine-learning engineers tools to find, access and reuse training data across internal programs and customer deployments. We are looking for a Staff Engineer to build the services behind those workflows. You will design and implement data APIs, dataset versioning, search and metadata systems that remain useful as datasets grow and schemas change. This role combines technical leadership with substantial hands-on software development. What you'll do:

What you'll do: Build dataset discovery, catalog and retrieval services, including LanceDB integration for indexing and search. Create APIs that let developers pin an exact dataset version and retrieve only the data they are authorized to access.

Build dataset discovery, catalog and retrieval services, including LanceDB integration for indexing and search. Create APIs that let developers pin an exact dataset version and retrieve only the data they are authorized to access. Track where data came from and how it changed so engineers can understand and reproduce training results.

What you’ll bring

All qualifications

Core experience

Experience designing and implementing production data platforms or data-intensive backend services.
Experience in any of the following is beneficial but not required:
Experience with data indexing, versioning, metadata, storage and access control.
Experience with LanceDB, Arrow, Parquet or comparable columnar and vector-data systems.
Experience evolving schemas or APIs while supporting existing users and historical data.
Experience with dataset catalogs, provenance or reproducible machine-learning workflows.

Qualification wording

Experience designing and implementing production data platforms or data-intensive backend services.

Experience in any of the following is beneficial but not required:

Experience with data indexing, versioning, metadata, storage and access control.

Experience with LanceDB, Arrow, Parquet or comparable columnar and vector-data systems.

Experience evolving schemas or APIs while supporting existing users and historical data.

Experience with dataset catalogs, provenance or reproducible machine-learning workflows.

Apply at Shieldai

Posting record

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Status in our records: Live
First seen by us: Aug 28, 202667 days ago
Recorded sightings: 135
Last seen by us: Nov 4, 2026
Employer says posted: Aug 26, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$200K–$300K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 67

Up longer than most. Similar jobs usually come down between day 6 and day 54.

From 10,782 similar postings that came down. Coming down is not always a hire.

Shieldai is hiring

11 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Data Engineer hiring is picking up
Its jobs tend to stay up a long time

Hiring record

See how this role fits your experience

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Where the posting names them

- Experience designing and implementing production data platforms or data-intensive backend services. - Strong software engineering skills in Python or a comparable backend language. - Experience with data indexing, versioning, metadata, storage and access control.

- Experience applying domain models or ontologies to practical data relationships and schema evolution. - Experience deploying data services on Kubernetes or in on-premises and disconnected environments. Why join us:

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

Job Description:

Reproducing a model’s results starts with knowing exactly which data it used. Shield AI’s AI Factory gives machine-learning engineers tools to find, access and reuse training data across internal programs and customer deployments.

We are looking for a Staff Engineer to build the services behind those workflows. You will design and implement data APIs, dataset versioning, search and metadata systems that remain useful as datasets grow and schemas change. This role combines technical leadership with substantial hands-on software development.

What you'll do:

Build dataset discovery, catalog and retrieval services, including LanceDB integration for indexing and search.

Create APIs that let developers pin an exact dataset version and retrieve only the data they are authorized to access.

Track where data came from and how it changed so engineers can understand and reproduce training results.

Design schema validation, compatibility and migration mechanisms that preserve access to historical datasets.

Define common identifiers and metadata relationships that connect datasets to experiments and model artifacts.

Work with machine-learning engineers to understand how they create and use datasets, then turn recurring needs into reusable tools.

Deliver reliable data services with tested upgrades, clear diagnostics and support for large datasets.

Key outcomes:

Developers can find and retrieve the right dataset without assembling a new data pipeline for each experiment.

Training runs can reference exact dataset versions and trace them back to their sources.

Schema changes have explicit compatibility or migration paths for existing users.

Data services work across multiple model-development workflows and deployment environments.

Required qualifications:

Experience designing and implementing production data platforms or data-intensive backend services.

Strong software engineering skills in Python or a comparable backend language.

Experience with data indexing, versioning, metadata, storage and access control.

Experience evolving schemas or APIs while supporting existing users and historical data.

Ability to lead technical design and implement substantial parts of the system.

Ability to work with data or machine-learning users and translate their needs into reliable services.

Bonus qualifications and relevant technologies:

Experience in any of the following is beneficial but not required:

Experience with LanceDB, Arrow, Parquet or comparable columnar and vector-data systems.

Experience with dataset catalogs, provenance or reproducible machine-learning workflows.

Experience applying domain models or ontologies to practical data relationships and schema evolution.

Experience deploying data services on Kubernetes or in on-premises and disconnected environments.

Why join us:

The Data Platform is foundational to how Shield AI builds, evaluates, certifies, and improves autonomy. This role offers the opportunity to shape both a core internal platform and a reference architecture delivered into demanding customer environments.

Your work will determine how effectively engineers and agents can find trusted context, understand provenance, aggregate data from distributed systems, and turn operational experience into better intelligent systems. You will work at the intersection of data systems, AI infrastructure, autonomy, distributed computing, and defense while helping establish the architecture that supports the next generation of mission-critical AI development.

Salary

200,000 – 300,000 USD per year

#LI-DM2

#LD

Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Employment type

Full Time Employee

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