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Salary
≈ $51k – $106k per year (Estimated)
Location
In office (Noida)
Seniority
Architect · 12+ years exp

First seen by Alion on Sep 24, 2026.

Overview
Company
Impact
Profile match
XEBO. ai is an AI-powered experience management platform that helps organizations collect, analyze, and act on feedback from customers, employees, and market research participants to improve engagement.

As the CTO, you will define and execute the company's technology vision, drive engineering excellence, and build scalable, secure, AI-first products. You will work closely with product, data science, business, and leadership teams to shape the technology roadmap while building high-performing engineering teams.

This role is ideal for a technology leader with deep expertise in enterprise SaaS, cloud architecture, AI/ML, and scaling engineering organizations in high-growth environments.

The core responsibilities for the job include the following:

Technology Strategy and Leadership:

  • Define and execute the long-term technology vision aligned with business objectives.
  • Drive technology roadmap, architecture, and platform scalability.
  • Evaluate emerging technologies and identify opportunities to create competitive advantage.
  • Lead innovation across AI, machine learning, cloud, automation, and analytics.

Engineering and Platform Architecture:

  • Own the architecture, scalability, reliability, and performance of the XEBO. ai platform.
  • Build secure, enterprise-grade SaaS applications and distributed systems.
  • Drive engineering best practices, coding standards, CI/CD, DevOps, and cloud modernization.
  • Ensure high availability, performance optimization, and platform security.

AI and Product Innovation:

  • Partner with Product, Data Science, and Design teams to deliver AI-powered customer experience solutions.
  • Lead development and deployment of AI/ML models and intelligent automation capabilities.
  • Drive innovation in generative AI, NLP, LLMs, predictive analytics, and conversational AI.
  • Establish responsible AI implementation and scalable AI infrastructure.

Leadership and Team Building:

  • Build, mentor, and scale high-performing engineering teams across backend, frontend, DevOps, QA, data engineering, and AI.
  • Foster a culture of innovation, ownership, collaboration, and continuous learning.
  • Drive cross-functional collaboration with product, sales, customer success, and business teams.
  • Attract and retain top engineering talent.

Security and Governance:

  • Ensure enterprise-grade security, compliance, and data privacy standards.
  • Oversee cybersecurity, infrastructure governance, disaster recovery, and risk management.
  • Manage technology budgets, cloud infrastructure costs, and strategic vendor partnerships.

Requirements:

  • Bachelor's or master's degree in computer science, engineering, or a related field.
  • 12+ years of experience in software engineering and technology leadership.
  • Proven experience as a CTO, VP of Engineering, Head of Engineering, or equivalent technology leadership role.
  • Strong experience building and scaling enterprise B2B SaaS platforms.
  • Deep expertise in AWS, Azure, or Google Cloud Platform.
  • Strong understanding of software architecture, distributed systems, APIs, databases, and cloud-native applications.
  • Experience leading engineering teams in startup or high-growth technology companies.
  • Hands-on knowledge of AI/ML technologies, analytics platforms, and data-driven products.
  • Excellent leadership, communication, stakeholder management, and strategic planning skills.

Preferred Qualifications:

  • Experience building customer experience (CX), surveys, feedback management, or analytics platforms.
  • Hands-on exposure to generative AI, large language models (LLMs), conversational AI, and intelligent automation.
  • Experience with microservices architecture and cloud-native engineering.
  • Understanding of enterprise integrations and scalable SaaS ecosystems.
  • Key Skills: Technology Strategy, CTO, Engineering Leadership, Enterprise SaaS, B2B SaaS, Software Architecture: Distributed Systems, Cloud Architecture: AWS, Azure, GCP, AI/ML, Generative AI LLMs, NLP, DevOps CI/CD, Microservices Platform Engineering, Product Engineering, Engineering Management, Team Building, Cybersecurity, Data Privacy, Customer Experience (CX), Analytics.
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