SDE II

About AiDASH

AiDASH is making critical infrastructure industries climate-resilient and sustainable with satellites and AI. Using our full-stack SaaS solutions, customers in electric, gas, water utilities, transportation, and construction are transforming asset inspection and maintenance - and complying with biodiversity net gain mandates and carbon capture goals. AiDASH exists to safeguard critical infrastructure and secure the future of humanAIty. Learn more at     

We are a Series C climate tech startup backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others.  We have been recognized by Forbes two years in a row as one of "America's Best Startup Employers."  We are also proud to be one of the few climate software companies in Time Magazine's "America's Top GreenTech Companies 2024". Deloitte Technology Fast 500 recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for

Join us in Securing Tomorrow

The Role

We are seeking a Backend Distributed Systems Engineer with strong computer science foundations and hands-on experience in building large-scale, microservice-based architectures. You will be responsible for designing and implementing reliable, scalable, and distributed backend systems for data-intensive applications. 

In this role, you will be building systems for our geospatialplatform that process terabytes of data and generate billions of featuresusing ML models with a very high frequency, powering customer-facing products that directly impact business value. The ideal candidate thrives in solving hard system problems, leverages AI-assisted tools for productivity, and has a strong eagerness to learn and adapt to emerging technologies.

• Design and build resilient, high-scale microservices in production environments 
• Develop and optimize large-scale data processing pipelines with Spark and modern data platform technologies 
• Build and scale systems that process terabytes of geospatial data and create billions of features for downstream use 
• Collaborate with cross-functional teams (Data, Platform, ML, Product) to deliver end-to-end solutions 
• Leverage AI-powered developer tools to boost productivity, automate workflows, and accelerate development cycles 
• Stay ahead of emerging technologies and contribute to architectural improvements 

• 2–5 years of experience in backend engineering, distributed systems, or data platforms 
• Strong computer science fundamentals: data structures, algorithms, OS, concurrency, networking 
• Proven experience building and operating resilient, high-scale microservices with container orchestration (Docker, Kubernetes) 
• Proficiency in at least one language: Python, Scala, or Java 
• Hands-on experience with modern data stack: Spark/Ray, SQL/NoSQL databases, caching, messaging systems (Kafka/Pulsar) 
• Experience with cloud environments (AWS/Azure/GCP) and CI/CD pipelines 
• Familiarity with observability tools (logging, metrics, tracing) and test-driven development (TDD) 
• Strong problem-solving mindset with a bias for action and continuous learning 

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work. 

We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs.