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Gen AI Engineer

Roles & Responsibilities

  • Strong proficiency in Python
  • Hands-on experience with Large Language Models (LLMs)
  • Experience integrating OpenAI APIs
  • Understanding of LLM lifecycle management

Requirements:

  • Design, build, and deploy AI-powered solutions
  • Work closely with product owners, architects, and data engineers
  • Deliver scalable and production-ready AI applications
  • Participate in occasional meetings and workshops at customer premises

Job description

Role Overview

INDICE is looking for a highly motivated Gen AI Engineer to join our growing team and help design, build, and deploy next-generation AI-powered solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and modern AI orchestration frameworks.

You will work closely with product owners, architects, data engineers, and customer stakeholders to deliver scalable and production-ready AI applications. This role is primarily remote, with occasional meetings and workshops required at customer premises in Athens.

Requirements

Programming

  • Strong proficiency in Python
  • Experience developing scalable backend services and AI integrations

Generative AI & LLMs

  • Hands-on experience with prompt engineering and LLM model usage
  • Experience integrating OpenAI APIs (Completions, Assistants) and similar AI services
  • Understanding of Retrieval-Augmented Generation (RAG) architectures
  • Experience integrating Azure AI Search or similar vector search technologies

AI Frameworks & Tooling

  • Experience with Microsoft Agent Framework, LangChain, Promptflow, or similar frameworks
  • Knowledge of AI orchestration pipelines and agent-based architectures

LLMOps

  • Understanding of LLM lifecycle management
  • Experience monitoring, evaluating, and optimizing Gen AI applications
  • Familiarity with model versioning, experimentation, and deployment processes

Additional Skills

  • Experience with C#, Java, or React is considered a strong advantage
  • Experience delivering traditional Machine Learning projects
  • Understanding of supervised and unsupervised learning techniques
  • Experience with model management and deployment pipelines
  • Knowledge of data preprocessing, feature engineering, and dataset preparation

Nice to Have

  • Experience with Microsoft Azure or other cloud platforms
  • Familiarity with cloud-native AI services
  • Experience with Infrastructure as Code (IaC)
  • Familiarity with CI/CD pipelines and automated deployments
  • Understanding of Responsible AI principles, governance, and ethical AI practices

Benefits

  • Opportunity to work on cutting-edge Gen AI projects
  • Flexible and mostly remote working model
  • Exposure to enterprise-scale AI implementations
  • Collaborative and innovation-driven environment
  • Continuous learning and professional development opportunities
  • Private Health insurance plan & personal equipment

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