AI Data Engineer

# AI Data Engineer Apply
** Job#: 3055798
***
* Job Description:

**** Backend AI Data Engineer
**** Remote
* *** Pay: $72.00 - $79.00
**** Role overview
** Team are seeking a hands-on senior backend engineer with deep expertise in data generation and processing, scalable pipelines, large-scale storage, and quantitative analysis. The ideal candidate combines strong software engineering fundamentals with practical experience building and maintaining reliable, cloud-based backend systems.

The candidate will take ownership of technical work from assessment and design through implementation and ongoing support. This role requires sound engineering judgment, comfort working in existing codebases, and the ability to translate evolving requirements into maintainable solutions while collaborating closely with engineering and cross-functional partners.
** About You
** You’re a self-driven backend engineer who cares about building reliable, scalable foundations for thoughtful product experiences. You can turn evolving ideas into maintainable services and data workflows, learn new tools quickly, and are comfortable exploring the unknown. You value strong engineering practices and know how to collaborate across engineering, design, and product.

You contribute openly, prototype or experiment to learn, share feedback generously, and help raise the quality of the team’s work. You are curious, adaptable, and motivated to build systems that make a real impact.
** Key responsibilities**→ Design, build, and evolve synthetic data-generation systems, assessing existing approaches and technical trade-offs while developing scalable, maintainable workflows that translate structured inputs, persona and organizational context into coherent, traceable, and reproducible datasets.→ Build and operate scalable pipelines and orchestration, applying concurrency, asynchronous execution, and resilient failure handling where appropriate.→ Design and evolve data models, storage approaches, and retrieval patterns to support large data volumes and efficient access.→

Develop and evolve validation frameworks and systems that define quality criteria, automate checks, and use quantitative analysis and profiling to assess data quality, investigate system behavior, and drive improvements in performance and reliability.→ Apply cloud engineering practices to build, deploy, monitor, and support dependable systems, balancing scalability, operational simplicity, and cost.→ Evaluate technical trade-offs, communicate progress and risks, and collaborate on practical solutions.

Maintain clear documentation, automated tests, and guidance that support ongoing ownership.
** Preferred Skills and Experience**→

Experience with Python→ Experience integrating LLMs through AI platforms, frameworks, and APIs, including building or evaluating production-oriented AI workflows.→ Experience designing and running evaluations of LLM output, such as defining quality criteria, building automated checks.

→ Experience with distributed processing, streaming or event-driven systems, and workflow orchestration tools—such as Apache Spark, Kafka, or equivalent technologies—and familiarity with relational or No

SQL databases, cloud object storage, or data lake architectures→

Experience with observability, performance tuning, and deployment automation is also valuable; no specific cloud provider or storage product is required→

Experience with Apache Spark, Kafka, or equivalent distributed-processing and event-driven technologies.→ Familiarity with relational or No

SQL databases, cloud object storage, and data lake architectures.→ Ability to work independently within an existing codebase and translate evolving requirements into maintainable solutions.→ Strong technical…