About NeuroscaleNeuroscale is building the AI recruiting operating system — one unified platform for your entire talent organization, from first touch to hired. Arbi eliminates fragmented workflows, integrates directly with your ATS, and orchestrates AI agents for sourcing, outreach, screening, and candidate intelligence end-to-end. By combining reasoning-optimized models with deep workflow automation, Arbi helps talent teams win more top candidates with dramatically less friction.We're backed by top operators and investors, and we're growing fast. Our momentum is further fueled by blue-chip partners and programs, including the NVIDIA Inception Program, the HPE Unleash AI Program, and our active DoD SBIR Phase II award and contract.We are looking for a Founding Data Engineer who can build the data backbone of the platform and help us scale reliably across ingestion, transformation, indexing, storage, and retrieval workflows. This is not a maintenance role. This is a hands-on, high-ownership opportunity for someone who has operated at a staff engineer, architect, or founding/lead engineer level and knows how to build production-grade systems that scale. You will work on the backbone of our platform: APIs, orchestration systems, data workflows, search infrastructure, background jobs, cloud deployment, and backend systems that power AI-enabled products for real customers.Role OverviewThis is a hands-on founding engineering role for someone who knows how to design, build, and operate production-grade data systems. You will work closely with backend engineers, AI engineers, and product leaders to create the data infrastructure that powers search, analytics, and AI-driven product experiences.You should be comfortable working in a fast-moving startup environment, making pragmatic technical decisions, and owning systems end to end.What You'll DoDesign, build, and maintain scalable batch and streaming data pipelines that support Neuroscale AI's core platformBuild robust ingestion, transformation, enrichment, and indexing workflows across structured, semi-structured, and document-centric dataDevelop and operate production-grade data systems using PostgreSQL, OpenSearch/Elasticsearch, AWS, and Python-based toolingDesign efficient data models, schemas, and storage patterns that support analytics, search, application workflows, and AI use casesBuild secure cloud-native data infrastructure using AWS services such as S3, Lambda, Glue, Kinesis, and IAMOptimize PostgreSQL for advanced SQL workloads, replication, query performance, and data integrityDesign and manage search and retrieval pipelines in OpenSearch/Elasticsearch for high-speed, relevant access to dataImprove observability, lineage, testing, and reliability across the data platformAutomate infrastructure provisioning and environment management using Terraform or CloudFormationPartner closely with backend, product, and AI teams to enable new data-driven capabilities and platform featuresHelp define engineering standards, data platform best practices, and operational playbooks as the company scalesRequirementsStrong experience in data engineering or backend/data platform engineering in production environmentsStrong programming skills in Python; experience with Typescript is a plusDeep hands-on experience with PostgreSQL, including advanced SQL, schema design, query tuning, indexes, sharding, replication, and modelingStrong experience with OpenSearch/Elasticsearch, including indexing strategy, search performance, relevance tuning, and distributed query operations at very large scaleExperience building and maintaining ETL/ELT pipelines and data processing workflows for large-scale datasetsHands-on experience with AWS data and infrastructure services, especially S3, Lambda, Glue, Kinesis, and IAMExperience designing reliable cloud-native data architectures and secure data movement patternsExperience with Infrastructure as Code, ideally Terraform or CloudFormationStrong understanding of distributed systems, production operations, fault tolerance, and data reliabilityAbility to work with high ownership, move quickly, and make sound engineering decisions in a startup environmentNice to HaveExperience with Kafka, event-driven systems, or other streaming architecturesExperience supporting vector search, semantic retrieval, or AI/ML data pipelinesExperience with workflow orchestration, async processing, and integration-heavy platformsExperience with containerized environments, CI/CD pipelines, and production monitoringExperience working on document-centric or AI-enabled platformsCompensation & BenefitsBase Salary: $100,000 – $200,000Equity: ~0.1–0.75% early-stage equity with a clear range shared during the processBonus: Quarterly performance bonuses tied to clear feature shipping targetsHealthcare: Medical, dental, and vision coveragePTO: 14 days accrued annuallyLearning: $2,000+ per year for courses, conferences, books, and communitiesEquipment: New MacBook Pro, monitor, and a monthly tools budgetFlexibility: 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 scalesWhy Join Neuroscale AIFounding role with significant ownership over architecture, tooling, and platform decisionsDirect exposure to company leadership with real influence over product directionWork on modern AI, search, and data infrastructure problems with direct customer impactBuild systems from day one — no legacy architecture to inheritZero bureaucracy, high trust, and a strong culture of ownership and technical excellenceA seat at the table as we scale our product, team, and engineering culture
10 days ago