AI Data Engineer 3

About the Role: We are seeking a highly skilled and passionate engineer to join a dynamic team dedicated to building innovative AI experiences. In this role, you will be a hands-on expert in data generation, processing, and scalable backend systems. You will play a pivotal part in designing and building modern, intelligent systems, collaborating closely with designers, product partners, and engineers. Your contributions will be critical in driving rapid prototyping, model tuning, data experiments, and AI-related explorations, ultimately evolving cutting-edge products. You are a self-driven professional who thrives on creating reliable, scalable foundations for thoughtful product experiences. You're adept at translating evolving ideas into maintainable services and data workflows, eager to learn new tools, and comfortable exploring uncharted territories. Your commitment to strong engineering practices and cross-functional collaboration will be key to your success in this impactful position.

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. What You'll Bring 5+ years of software or data engineering experience, or equivalent significant experience building systems with coding in languages & frameworks including, but not limited to, Python, Spring Boot, .NET, with demonstrated ownership through implementation and support. Strong backend programming and systems engineering skills, including designing maintainable services, modular components, APIs, and automated tests. Deep experience designing, building, and operating data generation, ETL, and distributed data-processing workflows, including creating, scaling, and maintaining cloud-based pipelines. Strong working understanding of large language models (LLMs), including their capabilities, limitations, common failure modes, and the role of data quality, prompting, evaluation, and model behavior in AI-powered systems. Working knowledge of orchestration, concurrency, asynchronous execution, streaming or event-driven architectures, and recovery from failures. Strong knowledge of large-scale data storage, modeling, and retrieval, including partitioning, indexing, access patterns, and trade-offs among storage approaches. Strong quantitative analytical and troubleshooting skills, with the ability to validate data and system behavior, interpret performance measurements, and make evidence-based engineering decisions. Practical cloud engineering experience and the ability to work independently in an existing codebase. Clear technical communication, effective collaboration, and a disciplined approach to documentation and operational reliability.

What Will Set You Apart: 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 and 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 NoSQL databases, cloud object storage, or data lake architectures. Experience with observability, performance tuning, and deployment automation. Ability to work independently within an existing codebase and translate evolving requirements into maintainable solutions. Strong technical communication, documentation, collaboration, adaptability, and problem-solving skills. Experience creating automated tests and data-quality validation frameworks.

Client Description: Join a global technology leader driving innovation and empowering people and organizations worldwide to achieve more. Here, you'll collaborate with passionate, diverse teams to create impactful solutions that shape the future. The culture prioritizes growth, inclusion, and purpose—where your ideas are valued, and your work drives real change. Wherever your passion lies and wherever your career is headed—you’ll play a role in projects that touch billions of lives. With flexible work options and a supportive environment, you'll have the tools to thrive both personally and professionally. Be part of something that truly matters. Why work with AQUENT? Check out our awesome benefits: https://aquent.com/talent/talent-benefitsAquent is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.