Data Engineering Specialist AI positions focus on delivering results in their domain. This page aggregates open Data Engineering Specialist AI roles and what employers typically expect.
Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we’re looking for a skilled Data Engineering Specialist – AI to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. # Data Engineering Specialist – AI **Job Title:** Data Engineering Specialist – AI **Location:** 100% Remote (Continental United States) **Position Type:** In-house Bright Vision Technologies SOW engagement (no third-party client or vendor) **Experience:** 6+ years **Salary Range :** $100k to $150k per annnum **Sponsorship:** No new H1B sponsorship available. H1B transfers welcomed for qualified candidates. **Employment Type:** Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party) **Engagement:** Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap **Compensation:** Competitive base salary commensurate with experience, plus benefits. **Employment Terms & Visa Policy** **This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.** **This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement.** The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved. We do not engage in C2C, 1099, or third-party arrangements for this role. **BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.** Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables. No new H1B sponsorship is available for this role. **However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.** For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience. **Job Summary** We are seeking an Data Engineering Specialist – AI to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency. **Key Responsibilities** - Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows. - Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals. - Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale. - Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training. - Build high-throughput data loading systems that maximize GPU utilization during training. - Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems. - Design storage architectures balancing cost, throughput, and latency across data tiers. - Build evaluation dataset construction pipelines with strict integrity and contamination controls. - Implement data privacy, redaction, and consent enforcement throughout the pipeline. - Collaborate with ML researchers an…