Lead Fullstack AI Development Engineer

Diebold Inc.; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Diebold Inc. in Hyderabad seeks a Lead Full-Stack Development Engineer with 8–12 years of deep software engineering and machine learning production experience.

You will drive the technical execution within the AI Product & Engineering team, designing, building, and deploying scalable, high-performance AI applications and robust production systems. You will lead end-to-end development, bridging AI research models, cloud data infrastructure, and user-facing software.

Qualifications

• 8–12 years of software engineering experience.
• Production experience with machine learning systems or platforms.
• Ability to design and deploy scalable AI applications and robust production systems.

Responsibilities

• Lead end-to-end development lifecycle for AI-enabled products.
• Architect resilient codebases and optimize inference pipelines.
• Implement modern user interfaces for enterprise applications.
• Establish automated DevOps guardrails to streamline deployment and monitoring.

Skills

Full-Stack development

Machine learning production

Software engineering

DevOps

UI development

Job description

We are seeking a highly talented and seasoned Lead Full-Stack Development Engineer with 8–12 years of
deep software engineering and machine learning production experience to drive the technical execution of our
AI product suites. Operating embedded directly within the AI Product & Engineering team, this pivotal role
serves as the primary engineering anchor responsible for designing, building, and deploying scalable,
high-performance AI applications, interactive user interfaces, and robust production systems.

You will lead the end-to-end development lifecycle, bridging the gap between foundational AI research models,
cloud data infrastructure, and user-facing software applications. Your core mission is to architect resilient
codebases, optimize inference pipelines, implement modern user interfaces, and establish automated DevOps
guardrails that seamlessly transform cognitive AI capabilities into enterprise-grade, scalable business solutions.