Generative AI Engineer

TL;DR

Generative AI Engineer (AI/ML): Designing, developing, and deploying AI/ML and Generative AI solutions with an accent on LLM integration, RAG frameworks, and intelligent automation. Focus on fine-tuning models for performance, building scalable AI agents, and collaborating across engineering teams to deliver robust AI-driven applications.

Company

hirify.global is a global edge-to-cloud company that helps organizations connect, protect, analyze, and act on their data.

What you will do

• Design, develop, and deploy end-to-end AI/ML and Generative AI solutions.
• Build and optimize machine learning models for prediction, classification, and automation.
• Develop AI applications leveraging Large Language Models and RAG frameworks.
• Create and maintain intelligent AI agents, chatbots, and automation workflows.
• Fine-tune and evaluate models to ensure accuracy, scalability, and performance.
• Collaborate with product, engineering, and business teams to deliver impactful AI-driven solutions.

Requirements

• 2–4 years of professional experience in AI/ML, Data Science, or Software Engineering.
• Strong programming proficiency in Python.
• Hands-on experience with Machine Learning, Deep Learning, and model development.
• Knowledge of Generative AI, LLMs, and prompt engineering techniques.
• Experience with frameworks such as LangChain, LlamaIndex, Hugging Face, PyTorch, or TensorFlow.
• Understanding of RAG architectures, vector databases, and embedding strategies.
• Must be able to work in a hybrid model with an expectation of 2 days per week in an HPE office.

Nice to have

• Experience with AI agents, cloud platforms, and MLOps.
• Knowledge of NLP, Computer Vision, or Conversational AI.
• Relevant certifications in AI or Data Science.

Culture & Benefits

• Comprehensive health and wellbeing benefits for employees and their families.
• Dedicated programs for personal and professional career development.
• Inclusive work environment that values diverse backgrounds and individual uniqueness.
• Flexibility to manage work and personal needs.
• Commitment to responsible AI practices and ethical innovation.