Lead AI Application Engineer- Business Technology

Mode Analytics; Thiruvananthapuram; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

ThoughtSpot is seeking an architect-level Lead Engineer in India to own greenfield internal tools replacing complex SaaS platforms. You will design scalable backend services, data models, and integrations, setting architectural standards for an AI-augmented team.

You’ll drive the full lifecycle from provisioning to production and mentor new graduates. You will directly collaborate with stakeholders to translate ambiguous requirements into concrete designs, build end-to-end CI/CD pipelines, and

Qualifications

• 7+ years building production-grade, full-stack applications (e.g., Python, Node.js, Go, React, relational and vector databases).
• Strong backend architecture and system design skills, with a proven ability to design distributed systems and to critically evaluate, refactor, and modularize sub-optimal code, including LLM-generated code.
• Core knowledge of Kubernetes, Docker, cloud platforms (AWS/GCP), and distributed systems, with experience running multi-service containerized environments in production.
• Demonstrated experience hosting and scaling internal applications from scratch, including building CI/CD pipelines end to end (GitHub Actions, GitLab CI, or Jenkins).
• Hands‑on experience with AI development tools and agentic coding workflows, and a record of using them to ship real products.
• Working knowledge of secure SDLC practices: automated static/dynamic code scanning, secret detection, and OWASP Top 10 awareness built into the pipeline.
• Strong communication and collaboration skills, with the ability to work directly with non-engineering stakeholders and turn use cases into shipped software.
• A track record of mentoring junior engineers.

Responsibilities

• Architect and design scalable backend services, data models, and integrations for internal tools that replace complex SaaS platforms. Set and enforce architectural standards across the team.
• Understand the business: Work directly with stakeholders to turn ambiguous requirements into clear technical designs, and make pragmatic build-vs-buy and scope trade-offs.
• Host and scale from scratch: Own the full lifecycle of internal applications: provisioning infrastructure, deploying, scaling, monitoring, and operating them in production.
• Own CI/CD: Build and maintain end-to-end pipelines with automated testing, code scanning, and branch-protection guardrails, making them the definitive quality gate for all code, including AI-generated code.
• Build with AI: Use tools like Claude Code and Cursor to accelerate delivery, and establish team practices for reviewing, refactoring, and hardening AI-generated code.
• Collaborate across teams: Partner with Sales, Pre-Sales, Project Management, and other internal teams to prioritize work, gather feedback, and iterate quickly.
• Mentor: Guide new graduates and junior engineers on architectural first principles, code quality, security, and effective AI-assisted development.

Skills

Backend architecture

System design

Kubernetes

Docker

Cloud platforms (AWS/GCP)

CI/CD pipelines

AI development tools

Secure SDLC practices

Mentoring

Communication

Tools

GitHub Actions

GitLab CI

Jenkins

CI/CD tooling

Job description

ThoughtSpot is a Data & AI platform that helps companies turn data into enterprise advantage. We're Gartner MQ leaders with more than 1,000 customers globally and offices in Mountain View, Chicago, London, Bangalore, Sydney, and Tokyo.

About the Role:

We’re building an in-house engineering team to replace major enterprise SaaS platforms with custom internal tools, designed and delivered with AI-augmented development. We’re looking for an architect-level Lead Engineer to own this initiative. You’ll lead a lean, AI-augmented team, define the technical blueprints, host and scale applications from scratch, and grow new college graduates into productive engineers. This is greenfield, end-to-end ownership with direct business impact: every tool you ship replaces a vendor we no longer need to pay.

What You’ll Do:

• Architect and design: Design scalable backend services, data models, and integrations for internal tools that replace complex SaaS platforms. Set and enforce architectural standards across the team.
• Understand the business: Work directly with stakeholders to turn ambiguous requirements into clear technical designs, and make pragmatic build-vs-buy and scope trade-offs.
• Host and scale from scratch: Own the full lifecycle of internal applications: provisioning infrastructure, deploying, scaling, monitoring, and operating them in production.
• Own CI/CD: Build and maintain end-to-end pipelines with automated testing, code scanning, and branch-protection guardrails, making them the definitive quality gate for all code, including AI-generated code.
• Build with AI: Use tools like Claude Code and Cursor to accelerate delivery, and establish team practices for reviewing, refactoring, and hardening AI-generated code.
• Collaborate across teams: Partner with Sales, Pre-Sales, Project Management, and other internal teams to prioritize work, gather feedback, and iterate quickly.
• Mentor: Guide new graduates and junior engineers on architectural first principles, code quality, security, and effective AI-assisted development.

What You Bring:

• 7+ years building production-grade, full-stack applications (e.g., Python, Node.js, Go, React, relational and vector databases).
• Strong backend architecture and system design skills, with a proven ability to design distributed systems and to critically evaluate, refactor, and modularize sub-optimal code, including LLM-generated code.
• Core knowledge of Kubernetes, Docker, cloud platforms (AWS/GCP), and distributed systems, with experience running multi-service containerized environments in production.
• Demonstrated experience hosting and scaling internal applications from scratch, including building CI/CD pipelines end to end (GitHub Actions, GitLab CI, or Jenkins).
• Hands‑on experience with AI development tools and agentic coding workflows, and a record of using them to ship real products.
• Working knowledge of secure SDLC practices: automated static/dynamic code scanning, secret detection, and OWASP Top 10 awareness built into the pipeline.
• Strong communication and collaboration skills, with the ability to work directly with non-engineering stakeholders and turn use cases into shipped software.
• A track record of mentoring junior engineers.