AI Engineer

 

• Minimum 3 years of professional experience in AI Engineering, Machine Learning, Generative AI, or a closely related field.

• Hands-on experience in developing, deploying, and maintaining AI solutions in production environments.

• Practical experience with enterprise software, SaaS platforms, or business applications will be considered an added advantage

  Skills & Area of Expertise

  • Minimum 3 years of professional experience in AI Engineering, Machine Learning, Generative AI, or a related field.

  • Hands-on experience developing, deploying, and maintaining AI solutions in production environments.

  • Experience with enterprise software, SaaS, or business applications will be an added advantage.

  • Strong practical knowledge of Machine Learning, Deep Learning, Generative AI, and LLM technologies.

  • Hands-on expertise in RAG, prompt engineering, vector databases, and AI agents.

  • Experience with computer vision and face recognition technologies is preferred.

  • Proficiency in AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or equivalent tools.

  • Familiarity with AI platforms including AWS Bedrock, OpenAI, Google Gemini, or similar services is an advantage.

  • Strong understanding of APIs, cloud platforms, databases, and AI application integration.

  • Knowledge of MLOps, model deployment, monitoring, version control, and model lifecycle management.

  • Strong analytical, problem-solving, communication, and collaboration skills.

  • Ability to work independently while effectively contributing to a fast-paced, cross-functional team.

  Programming Languages

  • Python — Required

  • JavaScript / TypeScript — Preferred

We are seeking a skilled AI Engineer to design, develop, integrate, and deploy intelligent solutions using Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). The role focuses on building practical, scalable AI applications that address real-world business and operational needs.

The selected candidate will work on AI agents, Retrieval-Augmented Generation (RAG) systems, intelligent automation, and computer vision solutions, while contributing to the integration and deployment of modern AI technologies across applications and business workflows.

Responsibilities

• Design, develop, and deploy Machine Learning, Deep Learning, and Generative AI solutions.

• Build AI-powered applications such as LLM applications, chatbots, AI agents, recommendation systems, predictive analytics, and workflow automation.

• Develop and integrate LLM-based solutions using models and platforms such as GPT, Claude, Gemini, Llama, and Mistral.

• Design and implement RAG systems, prompt engineering workflows, AI pipelines, and vector database solutions.

• Develop Face Detection, Face Recognition, and Face Verification solutions.

• Collect, preprocess, and analyze datasets and perform feature engineering for AI model development.

• Train, fine-tune, evaluate, and optimize AI models to improve accuracy, efficiency, and performance.

• Develop APIs and integrate AI solutions with web, mobile, and enterprise applications.

• Deploy, monitor, and maintain AI solutions using cloud platforms and containerization technologies.

• Apply MLOps practices for model versioning, monitoring, retraining, and deployment.

• Ensure AI applications are scalable, secure, reliable, and production-ready.

• Conduct proof-of-concepts (POCs) and assess emerging AI technologies for potential business applications.

• Collaborate with Software Engineers, QA Engineers, Data Engineers, Product Managers, and business teams.

• Maintain clear documentation of AI models, architectures, workflows, integrations, and development processes.