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ThoughtSpot

AI-powered analytics platform for data insights

Lead AI Application Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeThiruvananthapuram, Kerala, IndiaNo salary listed

About the Job

Requirements

  • At least 7 years of experience building production-grade, full-stack applications, with examples including Python, Node.js, Go, React, relational databases, and vector databases.
  • Strong backend architecture and system design skills, including designing distributed systems and critically evaluating, refactoring, and modularizing suboptimal code, including large language model-generated code.
  • Core knowledge of Kubernetes, Docker, cloud platforms such as AWS or Google Cloud Platform, and distributed systems, with experience running multi-service containerized environments in production.
  • Demonstrated experience hosting and scaling internal applications from scratch, including building continuous integration and continuous delivery pipelines end to end using GitHub Actions, GitLab CI, or Jenkins.
  • Hands-on experience with artificial intelligence development tools and agentic coding workflows, with a record of using them to ship products.
  • Working knowledge of secure software development lifecycle practices, including automated static and dynamic code scanning, secret detection, and awareness of the OWASP Top 10 integrated into pipelines.
  • Ability to work directly with non-engineering stakeholders and turn use cases into shipped software.
  • Ability to integrate artificial intelligence into daily workflows and use industry-leading large language models to increase productivity, automate routine tasks, and improve work quality.
  • Experience using artificial intelligence for research, content creation, and document summarization while retaining ownership of judgment and final decisions.
  • Ability to write effective prompts for artificial intelligence tools.
  • Curiosity in exploring new artificial intelligence tools, adaptability to learn and implement emerging technologies, and critical thinking to determine when to use artificial intelligence versus human judgment.

Responsibilities

  • Design scalable backend services, data models, and integrations for internal tools that replace complex software-as-a-service platforms, and set and enforce architectural standards across the team.
  • Work directly with stakeholders to turn ambiguous requirements into clear technical designs and make pragmatic build-versus-buy and scope trade-offs.
  • Own the full lifecycle of internal applications, including provisioning infrastructure, deploying, scaling, monitoring, and operating applications in production.
  • Build and maintain end-to-end continuous integration and continuous delivery pipelines with automated testing, code scanning, and branch-protection safeguards, serving as the quality gate for all code, including artificial intelligence-generated code.
  • Use tools such as Claude Code and Cursor to accelerate delivery, and establish team practices for reviewing, refactoring, and hardening artificial intelligence-generated code.
  • Partner with Sales, Pre-Sales, Project Management, and other internal teams to prioritize work, gather feedback, and iterate.
  • Guide new graduates and junior engineers on architectural first principles, code quality, security, and effective artificial intelligence-assisted development.
  • Experiment with ThoughtSpot artificial intelligence tools and leading industry large language models to streamline workflows, enhance output, and uncover insights.

About the Company

ThoughtSpot

AI-powered analytics platform for data insights

ThoughtSpot provides analytics and business intelligence tools that help people analyze data quickly. Its core product is an AI-powered analytics platform that lets users ask questions in plain language and get fast insights from large data sets. It also offers ThoughtSpot Embedded, which lets developers add analytics directly into their apps. The company uses a subscription-based model and offers services like training and support. ThoughtSpot differentiates itself with fast, AI-driven analytics that can turn large data collections (for example, Excel data spanning 45 days) into actionable insights in minutes, plus a strong community of users and developers that shares knowledge and skills. Its goal is to help organizations become data-fluent and make better decisions by making analytics easy to access and act on.

Company size
1,001-5,000
Company stage
Series F
Total funding
$643.7M
Headquarters
Mountain View, CA
Founded
2012

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