SDE II - Platform

Gurugram, Haryana, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Climate Tech, Utilities, Transportation, Construction, SaaSIndustries

Requirements

Candidates should have 2-5 years of experience in backend engineering, distributed systems, or data platforms, with strong computer science fundamentals including data structures, algorithms, OS, concurrency, and networking. Proven experience building and operating resilient, high-scale microservices with container orchestration (Docker, Kubernetes) is required. Proficiency in Python, Scala, or Java is necessary, along with hands-on experience in modern data stacks like Spark/Ray, SQL/NoSQL databases, caching, and messaging systems (Kafka/Pulsar). Experience with cloud environments (AWS/Azure/GCP), CI/CD pipelines, observability tools (logging, metrics, tracing), and test-driven development (TDD) is also expected. A strong problem-solving mindset with a bias for action and continuous learning is essential.

Responsibilities

The Backend Distributed Systems Engineer will design and build resilient, high-scale microservices in production environments. They will develop and optimize large-scale data processing pipelines using Spark and modern data platform technologies. Responsibilities include building and scaling systems that process terabytes of geospatial data and create billions of features for downstream use. The engineer will collaborate with cross-functional teams (Data, Platform, ML, Product) to deliver end-to-end solutions, leverage AI-powered developer tools to boost productivity, and stay ahead of emerging technologies to contribute to architectural improvements.

Skills

Distributed Systems

Microservices

Backend Development

Data Processing

Geospatial Platforms

Machine Learning

SaaS

AiDash

AI solutions for infrastructure management and sustainability

About AiDash

AiDash offers AI-driven solutions that assist industries in managing their infrastructure against climate change threats. Their main products include systems for vegetation management, sustainability management, integrity management, and climate risk intelligence, which utilize AI and satellite data to provide actionable insights. AiDash differentiates itself by focusing specifically on the needs of sectors with geographically distributed assets, such as utility and transportation companies. The company's goal is to enhance the efficiency and sustainability of critical infrastructure while reducing costs and risks associated with climate change.

Palo Alto, CaliforniaHeadquarters

2019Year Founded

$98.7MTotal Funding

SERIES_CCompany Stage

Data & Analytics, Energy, AI & Machine LearningIndustries

201-500Employees