Python Developer, GenAI – Agentic AI

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Nagarro

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

🤝 B2B

🏢 Enterprise

B2B • Enterprise • Technology Consulting

Nagarro is a global leader in digital engineering and technology consulting. The company helps clients become innovative, digital-first businesses by leveraging technology to drive business breakthroughs. Known for its entrepreneurial agility and CARING mindset, Nagarro offers a wide range of services, including digital engineering, intelligent enterprise solutions, and experience and design services. With over 17,900 employees across 37 countries, Nagarro collaborates with industry leaders to accelerate digitalization and technology-led innovation.

📋 Description

• Design, develop, and deploy AI-powered applications using Python. • Build and implement Generative AI solutions leveraging Large Language Models (LLMs). • Develop and orchestrate Agentic AI workflows, including autonomous agents capable of planning, reasoning, and executing tasks. • Integrate AI models with enterprise applications and external APIs. • Create robust prompts, retrieval pipelines, and agent architectures to solve business problems. • Optimize AI applications for performance, scalability, and reliability. • Collaborate with cross-functional teams to understand requirements and translate them into technical solutions. • Implement best practices for testing, monitoring, and deployment of AI applications. • Utilize Elasticsearch for indexing, searching, and retrieval use cases where applicable. • Stay current with emerging trends and advancements in GenAI and Agentic AI technologies.

🎯 Requirements

• Strong programming experience in Python. • Hands-on experience with Generative AI technologies and LLM-based application development. • Proven experience designing and implementing Agentic AI solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar. • Experience working with prompt engineering, RAG (Retrieval-Augmented Generation), and AI orchestration patterns. • Knowledge of integrating AI services and APIs from leading model providers. • Familiarity with vector databases and embeddings. • Strong problem-solving skills and understanding of software engineering best practices. • Good to Have: Experience with Elasticsearch for search and retrieval implementations. • Good to Have: Exposure to cloud platforms such as AWS, Azure, or Google Cloud. • Good to Have: Experience with containerization technologies such as Docker and Kubernetes. • Good to Have: Understanding of MLOps practices and AI application deployment.

🏖️ Benefits

• Flexible working hours and option to work from home. • Ergonomic workstations, subsidies for health services, sponsored sports events, etc. • Regular after-work sessions, shared breakfasts/lunches, summer and Christmas parties, team events, and more. • Flat hierarchies, high level of personal responsibility, international and diverse teams, friendly and supportive team spirit. • Focus on promoting both technical and personal growth to ensure employees stay up to date. • Modern office, dual monitors, ergonomic equipment, and excellent on-site infrastructure.