Head of Engineering – AI & SaaS Products

Quadrant IT Services; Hyderabad; Presencial; INR 5.000.000 - 8.000.000; Jornada completa

Descripción de la vacante

Quadrant IT Services Pvt Ltd. seeks a Head of Engineering – AI & SaaS Products to drive architecture, engineering, and delivery of next-generation software, including AI-native SaaS apps.

The role requires deep technical leadership, hands-on engineering, and strategic decision-making to enable scalable, secure, high-performance products. The incumbent will establish standards, mentor teams, and guide technology choices to create competitive advantages using AI, while ensuring timely delivery of

Formación

• 15+ years of software engineering experience.
• 7–10 years in technical leadership, architecture, or engineering management.
• Proven design and delivery of production-grade SaaS or enterprise apps.
• Hands-on experience with LLMs, RAG, and AI workflows.
• Strong system-architecture, tech selection, databases, APIs, cloud, and security expertise.
• Experience leading engineering teams and removing blockers.

Responsabilidades

• Lead architecture, engineering, development, and delivery of AI-native SaaS products.
• Set engineering standards, processes, and best practices.
• Mentor developers and drive a culture of technical excellence and accountability.
• Translate business goals into scalable technical solutions and competitive advantages.

Educación

Bachelor's or Master's degree in CS/Engineering

Herramientas

CI/CD

Descripción del empleo

Role Type: Full-Time | Senior Technology Leadership

Experience: 12-15+ years in software engineering, with at least 5 years in technical leadership, architecture, or engineering management

Industry Experience: AI- Native & AI-powered SaaS Products, Enterprise Products, SaaS Products

1. Role Overview

We are looking for an accomplished Head of Engineering – AI & SaaS Products to lead the architecture, engineering, development, and delivery of multiple next-generation software products, including AI-native SaaS applications.

This role requires a rare combination of deep technical expertise, hands-on engineering capabilities, architectural decision-making, AI innovation, and strong team leadership. The individual will be responsible for translating business objectives and product requirements into scalable technical solutions, selecting the right technologies, guiding development teams, and ensuring the successful delivery of secure, high-performance, market-ready products.

The ideal candidate is a technology leader who understands not only how to build software, but also what to build, why to build it, how to build it efficiently, and how to leverage AI to create a meaningful competitive advantage.

This individual will establish engineering standards, improve development processes, mentor developers, and create a culture of technical excellence, accountability, innovation, and continuous improvement.

6. Experience & Qualifications

Mandatory Requirements

• 15+ years of overall software engineering experience.
• At least 7–10 years in technical leadership, architecture, or engineering management.
• Proven experience designing and delivering production-grade SaaS or enterprise applications.
• Hands-on experience integrating LLMs, implementing RAG, and building agentic or tool-using AI workflows.
• Strong expertise in system architecture, technology selection, databases, APIs, cloud infrastructure, and security.
• Experience leading engineering teams, reviewing technical work, resolving blockers, and delivering multiple projects.
• Ability to remain hands-on with architecture, prototypes, and complex engineering challenges.
• Strong analytical, communication, decision-making, and stakeholder-management skills.

Preferred Qualifications

• Experience building AI-native SaaS products from architecture through production.
• Exposure to HR tech, recruitment, procurement, ERP/CRM integrations, or enterprise workflows.
• Experience with multi-tenant SaaS, enterprise security, model fine-tuning, or self-hosted AI.
• Experience establishing engineering teams, standards, CI/CD, and scalable delivery processes.
• Proven ability to turn emerging AI technologies into commercially valuable products.
• Relevant bachelor's or master's degree, or equivalent practical experience.