Senior Staff Engineer (Cloud-Native Gen AI Development)

👋🏼We're Nagarro

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500 experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Requirements

• Experience : 7.5+ Years

  
  

• Mandatory hands-on Python coding capability for building production-grade GenAI, ML, and RAG pipelines.

  
  

• Demonstrable experience in building agentic workflows, RAG optimizations, and scalable LLM integrations.

  
  

• Strong foundation in traditional ML and data science, including feature engineering, model tuning, and statistical evaluation.

  
  

• Proven experience using Compass AI services in production-grade projects.

  
  

• Experience in building and optimizing ML pipelines on Azure.

  
  

• Good command of the Arabic language (verbal and written) is a plus.

  
  

Responsibilities

• Lead the engineering, deployment, and scaling of enterprise-grade AI platforms, including Conversational AI, LLM-based agents, and multi-agent orchestration frameworks.

  
  

• Design, code, and implement reusable frameworks, APIs, and SDKs for scalable enterprise consumption of AI capabilities.

  
  

• Build production-grade GenAI/RAG/ML systems, implementing RAG pipelines, vector database integrations, and knowledge graph-based retrieval.

  
  

• Own MLOps for LLM/ML workloads, including CI/CD, monitoring, retraining, observability, performance tuning, and drift detection.

  
  

• Rapidly translate new research into applied solutions and experiment with emerging tools and techniques.

  
  

• Evaluate AI frameworks and recommend enterprise adoption strategies.

  
  

• Mentor and guide AI engineers, fostering a culture of experimentation and engineering excellence.

  
  

• Lead end-to-end delivery of AI projects, managing risks related to performance, model drift, latency, and integration.

  
  

• Ensure engineering quality through regular code and design reviews and coordinate with data scientists, platform teams, and stakeholders.

  
  

• Own UAT planning, test case development, defect triaging, and ensure production rollout readiness.

  
  

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.