BrightAI is a hyper-growth Infrastructure AIoT copilot platform company with a mission to revitalize and automate western infrastructure. Our commitment lies in empowering major infrastructure services companies through cutting-edge solutions encompassing autonomous monitoring, inspection, and close-loop control. These transformative tools are designed for universal retrofitting to legacy infrastructure, seamlessly augmented with frontline AI copilot capabilities. By leveraging BrightAI, our customers seamlessly deploy cost-effective AI endpoints numbering in the hundreds of thousands. We pride ourselves on being the trusted force behind our customers' frontline services, fostering proactivity, and driving down costs.
BrightAI is a hyper-growth Infrastructure AIoT copilot platform company with a mission to revitalize and automate western infrastructure. Our commitment lies in empowering major infrastructure services companies through cutting-edge solutions encompassing autonomous monitoring, inspection, and close-loop control. These transformative tools are designed for universal retrofitting to legacy infrastructure, seamlessly augmented with frontline AI copilot capabilities. By leveraging BrightAI, our customers seamlessly deploy cost-effective AI endpoints numbering in the hundreds of thousands. We pride ourselves on being the trusted force behind our customers' frontline services, fostering proactivity, and driving down costs.
Product: Stateful OS — edge + multimodal AI platform for infrastructure monitoring and autonomous operations
Scale: >250,000 AI endpoints across 25,000+ sites (reported)
Revenue milestone: $80M reported while bootstrapped
Funding: $15M seed (Nov 2024); $51M Series A (Jul 2025) reported
Company Overview
Problem Domain
Infrastructure monitoring, inspection, and autonomous operations for critical physical systems
Founded
2019
Industry
Software Development
Funding Track Record
Seed- Nov 2024
$15M
Raised after bootstrapping to reported revenue
Series A- Jul 18, 2025
$51M
Reported participation from BoxGroup, Marlinspike, VSC Ventures, Rsquared VC, Cooley LLP, and others
Investor Signal
“Backed by prominent venture firms including Upfront Ventures (seed) and Khosla Ventures & Inspired Capital (Series A)”
Founders
What we do
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Join the Team
Data Platform Engineer
On-SitePalo Alto, CA, US
On-Site • Palo Alto, CA, US
We are a high-growth company transforming how businesses operate by integrating AI, IoT, and cloud-native services into scalable, real-time platforms. As a
Platform Data Engineer
, you’ll play a critical role in building and maintaining the data infrastructure that powers our products, services, and insights.
You’ll join a multidisciplinary team focused on ingesting, processing, and managing massive streams of sensor and operational data across a wide array of devices—from drones and robots to industrial systems and smart environments.
Responsibilities
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
AI Researcher
ContractNovi Sad, RS
Contract • Novi Sad, RS
Software Engineer
InternshipAustin, US
Internship • Austin, US
DevOps Engineer
Part-timeBerlin, DE
Part-time • Berlin, DE
Technical Writer
Full-timeSan Francisco, US
Full-time • San Francisco, US
Software Engineer
ContractUtrecht, NL
Contract • Utrecht, NL
Product Designer
Part-timeNew York, US
Part-time • New York, US
Design, build, and maintain scalable, reliable, and high-throughput data ingestion pipelines for structured and semi-structured data.
Implement robust and secure data lake and SQL-based storage architectures optimized for performance and cost.
Develop and maintain internal tools and frameworks for data ingestion using Python, Golang, and SQL.
Collaborate cross-functionally with Cloud, Edge, Product, and AI teams to define data contracts, schemas, and retention policies.
Use AWS cloud infrastructure (including Argo Workflows, S3, Lambda, Glue, Kinesis, Athena, and RDS) to support end-to-end data workflows.
Employ Infrastructure-as-Code (IaC) practices using Terraform to manage data platform infrastructure.
Monitor data pipelines for quality, latency, and failures using tools such as CloudWatch, SumoLogic, or DataDog.
Continuously optimize storage, partitioning, and query performance across large-scale datasets.
Participate in architecture reviews and ensure the platform adheres to security, compliance, and best practice standards.
Skills And Qualifications
5+ years of professional experience in software engineering or data engineering.
Strong programming skills in Python and Golang.
Deep understanding of SQL and modern data lake architectures (e.g., using Parquet, Iceberg, or Delta Lake).
Hands-on experience with AWS services including but not limited to: S3, Lambda, Glue, Kinesis, Athena, and RDS.
Proficiency with Terraform for automating infrastructure deployment and management.
Experience working with real-time or batch data ingestion at scale, and designing fault-tolerant ETL/ELT pipelines.
Familiarity with event-driven architectures and messaging systems like Kafka or Kinesis.
Strong debugging and optimization skills across cloud, network, and application layers.
Excellent collaboration, communication, and documentation skills.
Bonus Points
Experience working with time-series or IoT sensor data at industrial scale.
Familiarity with analytics tools and data warehouse integration (e.g., Redshift, Snowflake).
Exposure to gRPC and protobuf-based data contracts.
Experience supporting ML pipelines and feature stores.
Working knowledge of Kubernetes concepts.
Prior startup experience and/or comfort working in fast-paced, iterative environments.
