Artificial Intelligence Engineer

Company Description

AI Platform for enterprises

Our AI platform seamlessly aligns with and extends Hub365, our powerful low-code platform, allowing businesses to unify automation, workflows, and intelligent decisioning through a cohesive ecosystem. At Ever Quint, you will be part of a team pushing the boundaries of AI, low-code engineering, and enterprise modernisation.

Role Description

Artificial Intelligence (AI) Engineer

As an AI Engineer, you will design, develop, and optimize advanced AI models and enterprise-grade intelligent systems. Your work will involve building scalable AI components, experimenting with LLMs, developing sophisticated prompting frameworks, and integrating models into production-ready applications that power our enterprise AI platform.

Key responsibilities include:

• Designing and implementing AI/ML models, algorithms, and pipelines.
• Developing and optimizing neural network architectures and machine learning systems.
• Building NLP components, LLM-based applications, and advanced prompting workflows.
• Working with embeddings, vector databases, and RAG pipelines for enterprise use cases.
• Collaborating with cross-functional engineering, product, and research teams to deliver integrated AI features within our enterprise platform.
• Conducting research to advance model performance, scalability, and reliability.
• Contributing to the evolution of our AI platform to drive rapid digital transformation for global enterprises.

Qualifications

Core Technical Skills

• Strong understanding of 

  Neural Networks

  , 

  Machine Learning fundamentals

  , and 

  Pattern Recognition

  .
• Proficiency in 

  Python

   and solid grounding in 

  Computer Science fundamentals

  .
• Experience with 

  Natural Language Processing (NLP)

   tools, libraries, and modern techniques.
• Ability to design, train, and optimize 

  ML/AI models

   for complex real-world problems.
• Hands-on experience with 

  AI frameworks

   such as TensorFlow, PyTorch, Keras, etc.
• Experience working with 

  vector databases

  , 

  embeddings

  , and 

  Retrieval-Augmented Generation (RAG)

   architectures.
• Familiarity with 

  LLMs, transformers, and foundation models

  —including experience with fine-tuning, prompt engineering, and evaluation techniques.

• Advanced Prompting Experience:

   Ability to craft, optimise, and systematise prompts for LLM-driven workflows, agentic systems, and enterprise-grade automation scenarios.

Core Technical Skills

• Knowledge of 

  MLOps

   tools such as MLflow, Weights & Biases, Kubeflow, Airflow, etc.
• Experience deploying models via 

  Docker

  , REST APIs, microservices, or cloud platforms (

  AWS/GCP/Azure

  ).
• Exposure to building 

  production-grade AI or data-driven applications

   is a strong plus.

Soft Skills

• Strong analytical thinking and problem-solving abilities.
• Ability to collaborate effectively across teams in a fast-paced environment.
• Curiosity, creativity, and a passion for continuous learning in AI.