Job highlights

- 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
- Mentor: Guide new graduates and junior engineers on architectural first principles,code quality,security,and effective AI-assisted development

Job Summary 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.

Responsibilities

- 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 current 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. In-Office at ThoughtSpot

Spotters are expected in-office 3+ days per week to be part of the energy of their local team. Momentum compounds when were in the room together with faster decisions, sharper problem-solving, and the kind of peer learning that doesnt happen over a screen. Being in-office is our default way of working, with flexibility available where its genuinely needed. Mandatory and Required Skills for All ThoughtSpot Roles

Spotters are expected to demonstrate AI literacy and workflow integration to include to the ability to:

- Comfortably and confidently integrate AI into their daily workflows to increase productivity and quality.
- Hands-on experience to leverage AI tools (industry-leading LLMs) to increase productivity, automate routine tasks, and improve work quality.
- Speak to the experience of using AI for research, content creation, and document summarization while maintaining ownership of judgment and final decisions.
- Write effective prompts to get the most accurate and creative results from AI tools.

Spotters are expected to exemplify these key traits and possess an AI Mindset:
- Curiosity in exploring new AI tools
- Adaptability to quickly learn and implement new, emerging AI technologies
- Critical thinking to know when to identify when AI should be used versus when human judgement is necessary

This combination of curiosity, adaptability, and discernment defines the AI mindset, and it s required for every role at ThoughtSpot. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead AI Application Engineer-Business Technology (Thiruvananthapuram)
🏢 ThoughtSpot
📍 Thiruvananthapuram