Neuroscale AI - Founding Data Engineer • PG/Opensearch
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Requirements
• Strong experience in data engineering or backend/data platform engineering in production environments • Strong programming skills in Python; experience with Typescript is a plus • Deep hands-on experience with PostgreSQL, including advanced SQL, schema design, query tuning, indexes, sharding, replication, and modeling • Strong experience with OpenSearch/Elasticsearch, including indexing strategy, search performance, relevance tuning, and distributed query operations at very large scale • Experience building and maintaining ETL/ELT pipelines and data processing workflows for large-scale datasets • Hands-on experience with AWS data and infrastructure services, especially S3, Lambda, Glue, Kinesis, and IAM • Experience designing reliable cloud-native data architectures and secure data movement patterns • Experience with Infrastructure as Code, ideally Terraform or CloudFormation • Strong understanding of distributed systems, production operations, fault tolerance, and data reliability • Ability to work with high ownership, move quickly, and make sound engineering decisions in a startup environment • Experience with Kafka, event-driven systems, or other streaming architectures • Experience supporting vector search, semantic retrieval, or AI/ML data pipelines • Experience with workflow orchestration, async processing, and integration-heavy platforms • Experience with containerized environments, CI/CD pipelines, and production monitoring • Experience working on document-centric or AI-enabled platforms
Responsibilities
• Design, build, and maintain scalable batch and streaming data pipelines that support Neuroscale AI's core platform • Build robust ingestion, transformation, enrichment, and indexing workflows across structured, semi-structured, and document-centric data • Develop and operate production-grade data systems using PostgreSQL, OpenSearch/Elasticsearch, AWS, and Python-based tooling • Design efficient data models, schemas, and storage patterns that support analytics, search, application workflows, and AI use cases • Build secure cloud-native data infrastructure using AWS services such as S3, Lambda, Glue, Kinesis, and IAM • Optimize PostgreSQL for advanced SQL workloads, replication, query performance, and data integrity • Design and manage search and retrieval pipelines in OpenSearch/Elasticsearch for high-speed, relevant access to data • Improve observability, lineage, testing, and reliability across the data platform • Automate infrastructure provisioning and environment management using Terraform or CloudFormation • Partner closely with backend, product, and AI teams to enable new data-driven capabilities and platform features • Help define engineering standards, data platform best practices, and operational playbooks as the company scales
Benefits
• Equity: ~0.1–0.75% early-stage equity with a clear range shared during the process • Equity: • Bonus: Quarterly performance bonuses tied to clear feature shipping targets • Bonus: • Healthcare: Medical, dental, and vision coverage • Healthcare: • PTO: 14 days accrued annually • Learning: $2,000+ per year for courses, conferences, books, and communities • Learning: • Equipment: New MacBook Pro, monitor, and a monthly tools budget • Equipment: • Flexibility: Flexible hours; ideally in-person in the Northern Virginia / Washington DC region (remote considered) • Flexibility: • Growth: Clear, fast-track path to Engineering Lead as the team scales • Growth: • Founding role with significant ownership over architecture, tooling, and platform decisions • Direct exposure to company leadership with real influence over product direction • Work on modern AI, search, and data infrastructure problems with direct customer impact • Build systems from day one — no legacy architecture to inherit • Zero bureaucracy, high trust, and a strong culture of ownership and technical excellence • A seat at the table as we scale our product, team, and engineering culture
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