Python Developer GenAI & Agentic AI

Posted 4 Days Ago
Be an Early Applicant
Hiring Remotely in RO
Remote
Mid level
Artificial Intelligence • Information Technology • Machine Learning • Software • Virtual Reality • Analytics
The Role
Develop, deploy, and optimize Python-based Generative AI and Agentic AI applications. Build LLM integrations, design autonomous agent workflows, implement retrieval pipelines (RAG), prompt engineering, and integrate with enterprise APIs. Collaborate with cross-functional teams, apply best practices for testing, monitoring, and deployment, and leverage vector databases and Elasticsearch where applicable.
Summary Generated by Built In
Company Description

👋🏼 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 (19,000+ experts across 34 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!

Job Description

We are seeking a highly skilled Python Developer with strong expertise in Generative AI and Agentic AI frameworks to join our team. The ideal candidate will have hands-on experience building intelligent AI solutions, integrating large language models (LLMs), and developing autonomous AI agents capable of reasoning and task execution. Experience with Elasticsearch is desirable.

  • 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.

Qualifications

  • 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.
  • Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Understanding of MLOps practices and AI application deployment.

Skills Required

  • 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 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.
  • Experience with Elasticsearch for search and retrieval implementations.
  • Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Understanding of MLOps practices and AI application deployment.

Nagarro Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nagarro and has not been reviewed or approved by Nagarro.

  • Pay Growth & Progression Compensation is at times described as competitive, with salary hikes and perks occurring on certain occasions. Better growth opportunities and compensation are also positioned as an advantage versus other service-based companies.
  • Flexible Benefits Work arrangements are framed around a “work-from-anywhere” mindset with flexitime and family-friendly working models. This flexibility appears to add meaningful value to the overall rewards package for many roles.
  • Healthcare Strength Medical, dental, and vision coverage are described as available for employees and dependents, alongside life insurance. Mental-health support is also included via an Employee Assistance Program (EAP).

Nagarro Insights

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The Company
HQ: Munich
19,994 Employees
Year Founded: 1996

What We Do

Nagarro helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and sustainable. Today, we are 19,000 experts across 36 countries, forming a Nation of Nagarrians, ready to help our customers succeed.

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