Founding Data Engineer – PG, Opensearch

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🕒 April 5

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Logo of Neuroscale AI

Neuroscale AI

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

Artificial Intelligence

Neuroscale AI is a company working in artificial intelligence. No additional company text was provided, so this description is based only on the name and implies a focus on AI technologies, research, or products.

📋 Description

• 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

🎯 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

🏖️ Benefits

• Base Salary: $100,000 – $200,000 • Equity: ~0.1–0.75% early-stage equity with a clear range shared during the process • Bonus: Quarterly performance bonuses tied to clear feature shipping targets • Healthcare: Medical, dental, and vision coverage • PTO: 14 days accrued annually • Learning: $2,000+ per year for courses, conferences, books, and communities • Equipment: New MacBook Pro, monitor, and a monthly tools budget • Flexibility: Flexible hours; ideally in-person in the Northern Virginia / Washington DC region (remote considered) • Growth: Clear, fast-track path to Engineering Lead as the team scales

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