Principal Software Engineer

Applies the principles of software engineering to the design, development, maintenance, testing and evaluation of software and computer systems. Works cross-functionally to understand business requirements, evaluate alternative approaches and ensure software and systems are designed to facilitate ease of use and seamless integration into the target environments. Incorporates state-of-the-art concepts, tools and practices to facilitate system functionality, security and continuous improvement.

The Principal Engineer role is an individual contributor role in the software product development organization who understands products, relevant domains, technologies and its applications. 

We are seeking highly experienced AI/ML Software Engineer to lead complex projects, architect enterprise-grade AI systems, and drive strategic initiatives. Collaborate with senior stakeholders, mentor engineering teams, and ensure successful delivery of AI solutions on a scale.

Why should you join Diebold Nixdorf?

Brightest minds + technology and innovation + business transformation  The people of Diebold Nixdorf are 23,000+ teammates of diverse talents and expertise in more than 130 countries, harnessing future technologies to deliver personalized, secure consumer experiences that connect people to commerce. Our culture is fueled by our values of collaboration, decisiveness, urgency, willingness to change, and accountability.

–Diebold Nixdorf is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.

** To all recruitment agencies: Diebold Nixdorf does not accept agency resumes. Please do not forward resumes to our jobs alias, Diebold Nixdorf employees or any other organization location. Diebold Nixdorf is not responsible for any fees related to unsolicited resumes**

We are a global Company operating in multiple Locations and Entities. As we are keen to find the best solution for our candidates several legal entities might be applicable for a Job offer. A List of our operating entities can be found here - https://www.dieboldnixdorf.com/en-us/about-us/global-locations

• Understand customer business needs and actively participate in designing products and value‑added AI, GenAI, and agentic AI services.
• Ensure timely delivery and excellent engineering quality across all AI and software deliverables.
• Define AI architecture, coding standards, and best practices for ML, LLM, RAG, and agentic AI systems.
• Architect and implement advanced AI/ML models for NLP, computer vision, predictive analytics, generative AI, and multi‑agent workflows.
• Design distributed, scalable, and high‑performance AI systems optimized for reliability and enterprise workloads.
• Oversee MLOps & Deployment activities including model deployment, monitoring, observability, and lifecycle management across cloud and on‑prem environments.
• Review requirements, design, and code; conduct technical workshops and drive architectural alignment across teams.
• Mentor, support, and motivate engineering teams to achieve technical excellence in AI/ML, Generative AI, and Agentic AI implementations.
• Collaborate with product and business teams to align AI initiatives with organizational goals and strategic roadmap.
• Act as a subject matter expert for AI/ML, GenAI, and agentic AI domains—adopting and integrating the latest frameworks, tools, and technologies.
• Work with QA leads to ensure engineering quality, performance, and release readiness for AI‑driven components.
• Evaluate emerging AI, GenAI, and agentic AI technologies and lead adoption of cutting‑edge frameworks, including responsible AI practices and guardrails for safe usage.
• End to end Product & feature development including effort estimations, design, coding, testing and automation
• Understand customer’s business needs, product non-functional requirements and drives estimation of development tasks 
• Designs, develops, tests, documents and drives the implementation of moderately to highly complex systems, considering impact on the broader landscape, systems and components.
• Ensures timely delivery and excellent quality of the deliverables for the product
• Able to represent the product team externally and /or other external technology body with confidence 
• Acts as subject matter expert for the domain, technologies and also able to adapt latest technologies, frameworks and tools quickly
• Reviewing requirements, design, code, use cases, unit tests within team
• Able to resolve technical problems and help team members with technical challenges
• Help assess team / engineering skills & capabilities and mentor, motivate team members for technical excellence
• The ability to work in global environment, partner effectively with cross-functional teams, and manage multiple priorities and deliverables concurrently

• Collaborates with senior members of development departments to share experiences and knowledge and to identify ways to simplify and integrate products

  
  

          Required Qualifications

• 13+ years of software engineering experience with at least 7+ years in AI/ML development, including generative AI and agentic AI systems.
• Full time Bachelor and/or master’s degree in engineering with a minimum of 60% grade
• Strong programming proficiency in Python with expertise in enterprise‑grade AI/ML and LLM applications.
• Deep experience with ML frameworks—TensorFlow, PyTorch, scikit‑learn, Keras—and modern GenAI/agentic AI frameworks such as Hugging Face, LangChain, LangGraph, or AutoGen.
• Proficiency in Machine Learning, Deep Learning, NLP, Generative AI, RAG architecture, vector search, and multi‑agent workflows.
• Experience developing, deploying, optimizing, and scaling AI/ML, LLM, and agentic AI models across cloud and on premise environments.
• Expertise in data engineering, feature engineering, embedding pipelines, and large‑scale data processing.
• Hands‑on experience with MLOps tools—Docker, Kubernetes, CI/CD, MLflow—and cloud platforms (AWS/GCP/Azure).

• Demonstrated experience leading and executing customer‑facing AI solutions, including solution design, model development, deployment, and post‑production optimization.

  
  
• Demonstrated ability and experience in the entire product development cycle: from requirements, effort estimation, design, implementation, test and to deployment and production support

• Strong problem-solving skills and the ability to think outside the box

  
  

  Preferred Qualifications

  
  

• Experience building enterprise AI platforms

  
  
• Experience in delivering scalable and high-performance services and applications with excellent quality 
• Experience with LLMs, prompt engineering, and retrieval-augmented generation (RAG) based system.

• Knowledge of GPU optimization, ONNX, TensorRT, and model compression techniques.

  
  

• Exposure to enterprise-grade AI deployments and compliance frameworks. 

  
  

• Experience with advanced topics like reinforcement learning, generative AI, and multimodal systems.

  
  

• Publications, patents, or open‑source contributions in AI/ML 

  
  

• Experience leading AI transformations in large organizations