Generative AI & Backend Engineer — Full-Time (WFO)

Generative AI & Backend Engineer — Full-Time (WFO, Hyderabad)

**Experience Required:** 3–4 Years

Role Overview

We are looking for a highly skilled Generative AI & Backend Engineer with strong expertise in both AI systems and backend engineering. The ideal candidate should be capable of architecting, developing, deploying, and optimizing scalable AI-powered applications and backend infrastructures across multiple products and domains.

One of the core projects involves building AI-powered personalization and content generation pipelines where users can upload images, names, and custom inputs to generate high-quality digital and printable outputs. The candidate should understand how to build complete AI workflows including generation pipelines, backend orchestration, template systems, asset processing, and scalable API infrastructures.

The role requires ownership across AI pipelines, backend systems, infrastructure, deployment, scalability, and production optimization. The candidate should be comfortable building production-grade AI systems beyond basic prompt engineering.

Key Responsibilities

• Design and develop scalable AI-powered systems and backend architectures.
• Build production-ready backend services, APIs, and orchestration systems.
• Research, evaluate, and implement suitable AI models, workflows, and engineering approaches.
• Develop reusable and scalable AI workflows for image generation, automation, personalization, and content processing systems.
• Build AI personalization pipelines where user inputs such as photos, names, styles, and custom data are processed into premium digital or printable outputs.
• Design template-based generation systems and dynamic content workflows.
• Implement image-processing, rendering, compositing, and generation pipelines.
• Integrate AI systems with frontend applications, databases, storage systems, and third-party services.
• Handle backend architecture including authentication, databases, async processing, queues, caching, storage systems, and scalability.
• Build secure, optimized, and maintainable REST APIs and backend services.
• Optimize AI inference speed, backend performance, GPU utilization, infrastructure reliability, and operational costs.
• Deploy and maintain GPU-based AI systems and backend infrastructure in production environments.
• Collaborate with frontend, product, design, and engineering teams for seamless integrations.
• Create technical documentation, API documentation, and scalable engineering workflows.
• Continuously improve system reliability, maintainability, scalability, and performance.

Example Workflow & Pipeline Responsibilities

• Accept and process user-uploaded inputs such as images, names, text, and custom personalization data.
• Validate, preprocess, and optimize uploaded assets for AI workflows.
• Trigger AI generation pipelines based on selected templates, styles, or workflows.
• Generate personalized outputs while maintaining quality, consistency, and identity preservation.
• Process and optimize final assets for digital usage or print-ready delivery.
• Manage orchestration pipelines, async processing queues, asset storage, and delivery systems.
• Ensure scalable handling of multiple concurrent AI generation requests.

Skills Required

• Strong experience with Generative AI systems and backend development.
• Strong Python programming experience.
• Experience building scalable backend systems using FastAPI, Django, Flask, or similar frameworks.
• Strong understanding of REST APIs, backend architecture, and microservices.
• Experience with PostgreSQL, MySQL, MongoDB, Redis, or similar databases and caching systems.
• Understanding of authentication systems, API security, and backend best practices.
• Experience with async processing, queues, WebSockets, background jobs, and scalable backend workflows.
• Experience with Docker, CI/CD pipelines, deployment workflows, and cloud infrastructure.
• Experience with AI frameworks and ecosystems such as Stable Diffusion, SDXL, LLMs, LangChain, OpenAI APIs, or similar technologies.
• Understanding of AI inference pipelines, optimization, and deployment workflows.
• Experience with image processing, compositing, rendering, or AI asset-generation systems.
• Experience with cloud platforms such as AWS, GCP, Azure, RunPod, or similar environments.
• Familiarity with scalable architecture, monitoring, logging, and production optimization.

Preferred Experience

• AI-powered SaaS or automation product development.
• Personalized AI systems, AI agents, or workflow automation platforms.
• Experience with image generation, LLMs, RAG systems, AI assistants, or multimodal AI systems.
• GPU optimization and inference acceleration techniques.
• Multi-step AI orchestration and workflow systems.
• Production AI monitoring, backend optimization, and infrastructure scaling.

Ownership Expectations

• Independently drive technical architecture and engineering decisions.
• Recommend scalable and production-ready workflows.
• Take ownership from prototype to production deployment.
• Balance experimentation with engineering stability and scalability.
• Optimize both infrastructure costs and system performance.
• Proactively improve reliability, maintainability, and engineering quality.

Deliverables

• End-to-end AI-powered workflows and backend systems.
• Scalable backend architecture and APIs.
• Production-ready deployment infrastructure.
• Optimized AI inference and backend performance.
• Reusable and scalable engineering systems.
• Technical documentation for integrations and maintenance.

Job Type

• Full-Time
• Work From Office (WFO)
• Hyderabad
• Long-term opportunity