Job Details

About the Company: Shoreline AI is an Industrial AI/IoT startup providing a cloud-native, subscription based SAAS solution to optimize asset performance and operational efficiency for industrial powertrains that drive critical operations in Oil & Gas, Manufacturing, and other industries. Shoreline's product is already deployed at very large enterprise customers that are seeing significant benefits in their operations by avoiding expensive and unplanned downtime, and improving safety of their sites. Shoreline platform includes an industrial wireless sensor that is easily installed in minutes and captures vibration data along with additional environmental data through its built-in sensors and external ports. The data is uploaded to the Shoreline cloud platform that provides AI/ML driven insights to customers along with powerful data visualization tools for human experts. The platform can also ingest data from other data sources such as Pi for process data or other environmental data enabling engineers to provide deeper insights into the plant operations. Shoreline AI has its headquarters in Campbell, California. For more information, please visit

About the Role: We are looking for a Senior Cloud Data Platform Engineer/Architect to play a critical role in building and maintaining the data infrastructure and platform that powers Shoreline AI's products and services. You will be part of a small core team being built in the San Francisco Bay Area to complement our Pune Engineering Center. For best consideration, please add a Cover Letter to your resume (or, tailor your resume to the specific requirements for this role).

Must Haves:

• Strong foundational knowledge of Computer Science and Software Engineering -- especially in the areas of Cloud Computing and Data Platforms.
• Deep understanding of foundational cloud computing concepts including architecture and underlying technologies for various services available for storage (e.g., object storage, SQL and NoSQL databases) and computing (containers, virtual machines, FaaS, workflow orchestration, etc.).
• Experience with AI Tools like Claude Code and learnt how to use them to accelerate your learning, and harness them effectively through full SDLC (requirements, architecture/design, coding, testing, deployment, operation).
• Platform-builder mindset through experience defining and building APIs and tools to help software developers and data scientists be productive.
• Willingness to work from office at our US headquarters (currently in Campbell) in the San Jose/San Francisco Bay Area.
• Authorized to work in the US (US Citizen/Green Card). We will consider H1-B transfers for exceptional candidates, but are unable to support new H1-B applications.

Responsibilities:

• Design, implement and maintain a scalable and secure data lake to handle both structured and semi-structured data, implement flexible data governance, and provide secure access to Data Scientists and Software Developers.
• Design and build the “Data API” on top of the Data Lake Platform to provide easy programmatic access to Developers to the available Data for processing, analytics, and visualization.
• Create data pipelines to ingest, clean, and transform data from multiple sources.
• Develop a strategy for easy creation and deployment of containerized applications.
• Develop and maintain internal tools and frameworks for data ingestion using Python and SQL.
• Monitor data pipelines and cloud infrastructure for availability, low latency, and data correctness.
• Collaborate cross-functionally to define data models, contracts, schemas, access, and retention policies.
• Embrace software development and deployment best-practices including continuous integration/continuous deployment (CI/CD), employing Infrastructure-as-Code (IaC), automated testing, etc.
• Learn and adapt to new cloud technologies and development best practices.
• Maintain a strong customer-first attitude, and ensure that all technical solutions focus on providing customer delight.
• Participate in architecture, design and code reviews and maintain a high-standard of quality, testing, documentation, and compliance with security standards.

Desired Skills:

• 5+ years of experience in architecting, designing, developing, and implementing cloud solutions on AWS platforms.
• 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.
• Hands-on experience with AWS services including but not limited to: S3, Lambda, API Gateway, Glue, Kinesis, Athena, and RDS.
• Previous experience building a data platform with technologies like Apache Iceberg, Trino, Apache Spark, Kafka, Parquet, etc.
• Excellent collaboration and communication skills and ability to work with remote teams.

Pay range and compensation package: [Insert pay range or compensation details here]

Equal Opportunity Statement: [Include a statement on commitment to diversity and inclusivity.]