Aerovy is the operating layer for hardware OEMs. We take the signals coming off equipment in mobility, industrial, material handling, and construction, and normalize them into one model for assets, components, health, and events that holds across brands and model years.
With Aerovy, OEMs:
Launch an AI ecosystem for their hardware: branded apps a manufacturer puts in front of its own customers, from the app that comes with the machine to connected services and subscription tiers
Elevate aftermarket service: the machine reports a fault, it's diagnosed, the right technician is dispatched with the right part, and the job is closed out and reported. First-time fix rates go up; time to acknowledgement and time to response come down
Cut warranty cost and service spend: predictive failure detection, automated triage, and AI-driven root-cause across their install base
We're a fast-paced startup building the digital infrastructure for the next generation of intelligent hardware. Founded in 2023 as a spinoff of research from Purdue University, we've grown from 5 full-time workers at the end of 2025 to 13 today, with ARR up 4x+ over the same period. We're backed by institutional VCs from Mudita Venture Partners, M25, Quorum Capital Partners, Knoll Ventures, and Purdue Ventures, and angels from Google, Tesla, Intel, Siemens +more.
Job Summary
As a staff software engineer at Aerovy, you’ll lead, architect, and deliver core components of our cloud platform, serving real-time applications across energy, IoT, telematics, and AI.
You’ll work on a modular extensible system that powers everything from EV fleets and battery platforms to industrial equipment and robotics. This is a hands-on, full-stack opportunity where you’ll own features end-to-end, from concept to launch, and work closely with a nimble, high-caliber team.
If you're excited about building high performance production systems, solving hard problems at scale, and shipping real value in a fast-moving environment, we’d love to talk.
Responsibilities
You will play a key role in architecting solutions, mentoring engineers, and driving technical excellence across our cloud-native platforms.
You will be expected to function independently and proactively.
You will be routinely given requirements and be accountable to drive delivery end-to-end.
You will be expected to derive clear actionable engineering requirements from customer requirements, market data, and product strategy.
Collaborate with cross-functional teams to deliver business-critical features and services
Provide mentorship and guidance to junior and mid-level engineers
Own the reliability, scalability, maintainability, and performance of critical production systems
Contribute to the long-term technical vision and roadmap of our platform aligned with product strategy and business needs
Job Requirements
Bachelor or Master of Science in Computer Science or related fields with 5 or more years of industry experience
Passion for finding and solving hard problems
Passion for learning and growing both technically and non-technically
Strong understanding of distributed systems, micro-service architectures, RESTful APIs, and event-driven systems
Extensive experience in Cloud/IaaC Infrastructure and Tooling preferably AWS (EC2, Lambda, S3, RDS, AWS Batch, DynamoDB, CloudFormation/CDK, etc.)
Excellent communication skills and proven ability to convey complex ideas to diverse stakeholders in a concise and clear manner
Designed, developed and maintained high-performance services and software infrastructure using AWS or equivalent cloud services
Lead technical design and architecture discussions across multiple systems and teams
Championed engineering best practices, including CI/CD, monitoring, testing, and code quality
We are looking for a candidate with a proven track record shipping production systems to lead the development of a scalable, secure, and high-performance platform
Production experience in Cloud/IaaC Infrastructure and Tooling preferably AWS (EC2, ECS, Lambda, S3, DynamoDB, CloudFormation/CDK, etc.)
Production experience in Docker/containerized applications
Production experience with near real-time/real-time analytics, time series databases
Production experience with MQTT
This is an in person role in Seattle with hybrid opportunities available on a case-by-case basis, offering flexibility while ensuring close collaboration with product, engineering, and business stakeholders.