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Jobs (8)

0 AI · 14 total active
FilteredFunctionEngineering×
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AllEngineering · 8Product · 6
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Member of Technical Staff 2
This role focuses on building and enhancing frontend and backend systems for an AI-powered analytics platform. While the company heavily emphasizes AI literacy and the use of AI tools for productivity across all roles, the core responsibilities of this specific position involve traditional software engineering tasks such as feature development, coding, debugging, and system architecture collaboration. The role requires 1-2 years of experience in modern programming languages and a strong CS foundation. The company's product is an 'Agentic Analytics Platform' which implies AI is integral to the product, but the role itself is not directly building or researching AI models or systems.
—EngineeringMountain View, CA1w ago5
Senior Member of Technical Staff
Senior Engineer to join Cloud Platform team, taking ownership of architecture and evolution of a multi-tenant SaaS platform. Focus on backend engineering and cloud infrastructure, designing and building systems for control plane and data plane at scale. Role involves technical leadership, architecture decisions, mentoring, and partnering with product/infrastructure leaders.
—EngineeringMountain View, CA2w ago5
Site Reliability Engineering
This Site Reliability Engineering role focuses on ensuring the reliability of a SaaS platform by leveraging AI/ML for proactive observability, predictive anomaly detection, and intelligent alerting. The role also involves customer-facing technical support and incident management, with a strong emphasis on integrating AI tools into daily SRE workflows.
ServeEngineeringBangalore, India3w ago5
Member of Technical Staff
This role focuses on building and scaling SQL generation pipelines to transform raw information into actionable intelligence. It involves developing backend systems, improving query accuracy and performance, and incorporating AI/ML and LLM trends into query generation solutions. The role requires strong software engineering skills, proficiency in Java and SQL, and experience with distributed systems and AWS.
—EngineeringBangalore, India4w ago5
Member of Technical Staff 3
This role is for a frontend engineer at an AI-driven analytics company. The engineer will build frontend experiences for intelligent analytics products, working across the stack from API to UI. While the company is AI-driven and employees are expected to use AI tools in their daily workflow, the core craft of this role is frontend engineering, not building AI models or systems.
—EngineeringHyderabad, India5w ago5
Principal Engineer
Principal Engineer to own the architecture and evolution of a multi-tenant SaaS cloud platform, focusing on control plane and data plane systems, distributed systems, and cloud infrastructure. The role involves designing, building, and mentoring, with a strong emphasis on using AI coding assistants for infrastructure tasks.
—EngineeringBangalore, India5w ago5
Senior Manager, Engineering
This role is for a Senior Manager, Engineering at ThoughtSpot, focusing on the Liveboard platform. The responsibilities include technical leadership in architecture, scalability, and performance, partnering with Product on AI-driven insights and personalization, and leading a team for execution and delivery. A significant emphasis is placed on AI literacy and integrating AI tools into daily workflows for productivity and quality, although the core craft is not AI/ML model building.
—EngineeringTrivandrum, IndiaFeb 285
Member of Technical Staff 3
This role is for a Member of Technical Staff 3 on the Cloud Platform team, focusing on the development, operation, and reliability of a multi-tenant SaaS platform. Responsibilities include building and maintaining backend systems and cloud infrastructure, implementing features for tenant provisioning and cluster operations, writing production-quality code, debugging production issues, and improving system reliability and operability. The role requires hands-on experience with cloud platforms (AWS, GCP, Azure), infrastructure as code, containerized workloads, backend programming, distributed systems, and observability tools. A key aspect is the mandatory integration and use of AI coding assistants and AI tools in daily workflows to enhance productivity and quality, demonstrating an 'AI mindset' with curiosity, adaptability, and critical thinking.
—EngineeringBangalore, India3w ago1