Founding Data Engineer (PostgreSQL/OpenSearch)

TL;DR

Founding Data Engineer (PostgreSQL/OpenSearch): Build scalable batch and streaming data pipelines, ingestion, transformation, indexing, and retrieval workflows for AI recruiting platform with an accent on production-grade data systems using Postgres, OpenSearch, and AWS. Focus on designing efficient data models, optimizing query performance, search relevance, and ensuring reliability, observability, and fault tolerance at scale.

Location: Remote (ideally in-person in Northern Virginia / Washington DC region)

Salary: $100,000 – $200,000

Company

Neuroscale is building an AI recruiting operating system that unifies talent workflows, integrates with ATS, and orchestrates AI agents for sourcing, outreach, screening, and candidate intelligence.

What you will do

• Design, build, and maintain scalable batch and streaming data pipelines supporting core platform features
• Develop ingestion, transformation, enrichment, and indexing workflows for structured, semi-structured, and document data
• Operate production-grade data systems with PostgreSQL, OpenSearch/Elasticsearch, AWS, and Python tooling
• Design data models, schemas, and storage for analytics, search, workflows, and AI use cases
• Build secure cloud-native infrastructure using AWS S3, Lambda, Glue, Kinesis, and IAM
• Optimize Postgres for SQL workloads, replication, performance; manage OpenSearch pipelines for high-speed retrieval
• Improve observability, lineage, testing, reliability; automate IaC with Terraform/CloudFormation
• Partner with backend, product, and AI teams to enable data-driven features and define engineering standards

Requirements

• Strong experience in data engineering or backend/data platform engineering in production
• Strong Python programming; Typescript plus
• Deep hands-on with PostgreSQL: advanced SQL, schema design, query tuning, indexes, sharding, replication
• Strong OpenSearch/Elasticsearch: indexing, search performance, relevance tuning, distributed queries at scale
• ETL/ELT pipelines and data processing for large-scale datasets
• Hands-on AWS data services: S3, Lambda, Glue, Kinesis, IAM
• Reliable cloud-native architectures, secure data movement, IaC (Terraform/CloudFormation)
• Distributed systems, operations, fault tolerance, data reliability; high ownership in startup

Nice to have

• Kafka, event-driven or streaming architectures
• Vector search, semantic retrieval, AI/ML data pipelines
• Workflow orchestration, async processing, integration platforms
• Containerized environments, CI/CD, production monitoring
• Document-centric or AI-enabled platforms

Culture & Benefits

• Base salary $100k–$200k, equity ~0.1–0.75%, quarterly bonuses
• Medical, dental, vision healthcare; 14 days PTO annually
• $2,000+ yearly learning budget for courses, conferences, books
• New MacBook Pro, monitor, monthly tools budget
• Flexible hours; fast-track to Engineering Lead
• High trust, ownership, technical excellence; no bureaucracy