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Blueberry Labs - Technology Head - Generative AI

BLUEBERRY LABS PTE. LTD.
10 - 15 Years
Hyderabad

Posted on: 13/11/2026

Job Description

Head of Technology - Generative AI

Company: Template.net

Location: Hyderabad, India

Employment Type: Full-Time

Experience: 10+ Years (including 3+ years in senior engineering leadership)

About Template.net:

Template.net is an AI-native creation platform used by more than 4 million people worldwide every month.

Users simply describe what they need, and Template.net turns their ideas into finished, editable designs, videos, presentations, documents, and other creative content all in one place, from prompt to ready-to-use output in minutes.

We are a global product and technology company building the next generation of AI-first creation tools for individuals, creators, professionals, and businesses.

Our vision is to make AI-powered content creation faster, easier, more affordable, and accessible to everyone.

About the Role:

We are looking for an experienced, energetic, and technology-driven Head of Technology to lead the technology and engineering function for Template.net. The ideal candidate should have strong technical leadership, excellent problem-solving skills, and hands-on experience with modern web technologies and AI. The person will be responsible for driving the technology roadmap, building scalable products, and leading a high-performing engineering team.

The ideal candidate is a technology builder who can turn emerging AI capabilities into powerful, reliable products used by millions of people.

Key Responsibilities:

- Technology Leadership & Architecture: Own and drive the overall technology strategy, architecture, and engineering execution. Design highly scalable, reliable, secure, and cost-efficient systems capable of supporting millions of users. Lead frontend, backend, AI engineering, infrastructure, and platform development. Make critical architectural decisions balancing scalability, performance, development speed, and cost. Establish strong engineering standards, code quality, testing, deployment, and monitoring practices.

- Generative AI Engineering: Lead the integration and orchestration of leading LLMs and image, video, audio, and multimodal generation models. Build production-ready AI generation pipelines for designs, documents, presentations, images, videos, and other content formats. Develop intelligent model routing, prompt orchestration, structured generation, and multimodal workflows. Continuously evaluate and adopt emerging models, APIs, and AI technologies. Improve output accuracy, visual quality, consistency, editability, and generation reliability. Implement AI evaluation frameworks, automated quality checks, safety systems, and failure-recovery mechanisms.

- AI Inference & Cost Optimization: Optimize model selection, inference costs, latency, throughput, and generation success rates. Design efficient infrastructure for high-volume AI generation. Implement caching, queuing, asynchronous processing, intelligent retries, and fallback mechanisms. Evaluate third-party AI providers, direct model APIs, and self-hosted models where commercially appropriate. Balance AI output quality, generation speed, and unit economics to support profitable product growth.

- Product Engineering & Development: Lead the development of modern, high-performance web applications and AI-powered creative editors. Build systems that convert AI-generated outputs into editable, structured content. Oversee real-time editing, collaboration, asset processing, rendering, storage, and export pipelines. Work closely with product, design, and business leadership to translate product vision into production-ready features. Ensure rapid feature delivery without compromising performance, reliability, or user experience.

- Cloud Infrastructure, Scalability & Security: Own cloud architecture, infrastructure operations, deployment pipelines, and production reliability. Improve application response times, API performance, content delivery, database efficiency, and scalability. Establish monitoring, observability, incident management, and disaster recovery practices. Implement strong application security, data protection, access controls, and AI content safety measures. Drive continuous optimization of infrastructure and operational costs.

- Engineering Team Leadership: Build, mentor, and lead a high-performing team of AI engineers, frontend developers, backend developers, DevOps engineers, and QA engineers. Recruit exceptional technical talent and establish clear accountability across engineering functions. Set engineering priorities, development processes, architecture standards, and delivery milestones. Foster a culture of technical excellence, innovation, ownership, and execution. Remain technically hands-on and capable of reviewing architecture, debugging critical issues, and guiding complex engineering decisions.

Required Qualifications:

- 10+ years of software engineering experience, including substantial engineering leadership experience.

- Proven experience designing, building, and scaling production-grade SaaS or consumer internet platforms.

- Strong hands-on experience integrating LLMs and generative AI models into real-world products.

- Deep understanding of AI inference, multimodal generation, model APIs, prompt orchestration, and AI system evaluation.

- Strong proficiency in JavaScript, TypeScript, Node.js, React, and modern web application architectures.

- Working knowledge of Python and AI/ML engineering ecosystems.

- Expertise in distributed systems, API architecture, databases, cloud infrastructure, caching, and performance optimization.

Preferred Experience:

- Building AI-native products or platforms used by large consumer audiences.

- Experience with OpenAI, Google Gemini, Anthropic, and other leading AI model providers.

- Working with image, video, audio, and multimodal generation pipelines.

- Experience with AI-powered design editors, visual document systems, graphics processing, or browser-based creative tools.

- Optimizing AI model inference costs at high request volumes.

- Familiarity with GPU infrastructure, open-source models, model serving, and self-hosted inference.

- Experience taking products from early development to millions of users.

- Background in high-growth SaaS, AI startups, or global consumer technology companies.

What Success Looks Like:

- Deliver high-quality AI capabilities rapidly and consistently.

- Improve generation quality, success rates, and user experience.

- Reduce AI inference costs without compromising quality.

- Improve application speed, uptime, scalability, and engineering reliability.

- Build a strong, accountable, high-performance engineering organization.

- Support business growth through better technology, faster innovation, and efficient engineering execution.

Why Join Template.net?:

- Build at scale: Work on an AI-native product already serving millions of users worldwide.

- Own the technology: Influence architecture, AI strategy, infrastructure, engineering, and long-term technical direction.

- Work on cutting-edge AI: Build real-world products using the latest language, image, video, and multimodal technologies.

- High-impact leadership: Work directly with company leadership to shape the future of AI-powered content creation.

- Global opportunity: Build technology used by individuals, creators, professionals, and businesses around the world.

Conclusion:

We are looking for a technology leader who doesn't just manage engineers but builds systems, solves difficult technical problems, moves fast, and delivers world-class AI products.

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Posted in

AI/ML

Functional Area

ML / DL Engineering

Job Code

1683270

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