Nagarro (Frankfurt: NA9) is a leader in digital product engineering and drives technology-led business breakthroughs.
Python Developer, GenAI – Agentic AI
Location
Germany
Posted
1 day ago
Salary
0
Seniority
Senior
Job Description
Python Developer, GenAI – Agentic AI
Nagarro
• 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.
Job 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.
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