Head of Engineering Department

Company Description

Omind is a leading pioneer in providing advanced AI, machine learning, and intelligent automation solutions. With a focus on enhancing customer experiences, Omind offers a comprehensive suite of Digital CXM products and Automation solutions. The company is dedicated to helping organizations collect, integrate, and act intelligently on customer needs, creating personalized and impactful interactions at scale. Omind is committed to driving innovation and empowering businesses to achieve sustainable success.

Job Description: Head of Engineering (AI & SaaS)

Position:
Head of Engineering – AI & SaaS

Department:
Technology / Engineering

Location:
Bangalore

Role Overview

The Head of Engineering (AI & SaaS) will lead the development of scalable SaaS products infused with AI and machine learning capabilities. This role involves strategic leadership, hands-on technical direction, and operational excellence to build high-performance engineering teams and ship intelligent, reliable, secure SaaS solutions. You will define the technology roadmap, ensure world-class engineering practices, and drive innovation across AI, platform engineering, and product delivery.

Key Responsibilities
1. Technical Leadership & Strategy

• Define and execute the technology strategy for AI-powered SaaS products.
• Build and scale engineering teams across AI/ML, backend, frontend, data engineering, and DevOps.
• Establish a long-term architectural vision balancing innovation, scalability, and maintainability.
• Evaluate emerging AI and SaaS technologies and drive their adoption.

2. AI & Machine Learning Excellence

• Lead development and deployment of AI/ML models, intelligent features, and automation workflows.
• Ensure robust MLOps practices: model training, testing, deployment, versioning, and monitoring.
• Implement responsible AI practices including data governance, model fairness, and compliance (GDPR, SOC 2, etc.).
• Integrate LLMs, GenAI, NLP, or predictive analytics into SaaS workflows where impactful.

3. SaaS Platform Engineering

• Own architecture, infrastructure, and reliability of multi-tenant SaaS platforms.
• Ensure security, performance, scalability, and uptime to meet SaaS standards (SLAs/SLOs).
• Oversee cloud infrastructure (AWS, Azure, or GCP) and cost optimization.
• Guide teams in microservices design, API development, and distributed systems.

4. Engineering Operations & Delivery

• Establish engineering best practices (CI/CD, code quality, testing automation).
• Implement Agile processes ensuring fast iteration and predictable delivery.
• Set and track engineering KPIs (velocity, uptime, deployment frequency, model performance).
• Oversee technical documentation, release management, and continuous improvement.

5. Cross-Functional Collaboration

• Partner with Product Management to define roadmaps and translate business needs into technical requirements.
• Collaborate with Data, Design, and Customer Success teams to deliver impactful features.
• Communicate technical direction and progress clearly to executive leadership and stakeholders.

6. People Leadership

• Hire, mentor, and develop world-class engineering talent.
• Build a culture of innovation, accountability, transparency, and learning.
• Encourage experimentation with AI technologies while maintaining delivery discipline.

Qualifications
Education & Experience

• Bachelor's or Master's degree in Computer Science, Engineering.
• 10+ years of software engineering experience with 5+ years leading engineering teams.
• Proven experience building and scaling SaaS products and AI/ML-powered features.

Technical Skills

• Strong knowledge of AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, OpenAI APIs).
• Deep understanding of SaaS architecture, multi-tenancy, microservices, APIs, and distributed systems.
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps/DevOps tooling.
• Solid grasp of data engineering, ETL pipelines, data governance, and security best practices.

Leadership & Soft Skills

• Strategic thinker with strong decision-making and execution capabilities.
• Excellent communication skills with the ability to influence stakeholders at all levels.
• Ability to scale teams and processes in a high-growth SaaS environment.

Preferred Qualifications

• Experience developing AI-driven SaaS products (e.g., recommendation engines, LLM integrations, automation tools).
• Background in startup environments or scaling engineering teams from 0→1 or 1→100.
• Familiarity with compliance frameworks such as SOC 2, ISO 27001, GDPR.
• Experience with generative AI and fine-tuning LLMs.

What We Offer

• Competitive salary.
• Opportunity to lead AI innovation in a growing SaaS organization.
• High autonomy and influence over engineering culture and tech strategy.
• A collaborative, mission-driven environment with cutting-edge tools and technologies.