Job Description
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Job Title:  Senior Associate, AI Engineer
Posting Start Date:  24/07/2026
Job Description: 

Job Summary

The AI Engineer supports the development and implementation of AI and GenAI solutions, focusing on designing, building, and integrating AI applications to enhance customer experience, operational efficiency, and business outcomes, while collaborating with cross-functional teams and developing foundational capabilities in AI engineering, cloud platforms, and MLOps/LLMOps practices.

Job Responsibilities*

Accountability and activities
  1. Support the design, development, and deployment of AI/ML and Generative AI solutions, including AI applications, agents, and automation workflows for enterprise and telecom use cases
  1. Assist in building and enhancing AI platforms and services, including APIs, orchestration components, and foundational capabilities such as RAG, vector databases, and prompt engineering.
  1. Contribute to AI engineering and MLOps/LLMOps activities, including data pipeline development, model deployment, monitoring, and supporting governance, security, and compliance practices.
  1. Support the delivery of AI use cases across business domains (e.g., customer care, network operations, sales & marketing) by collaborating with cross-functional teams to gather requirements and implement solutions.
  1. Collaborate with internal teams and technology partners to support AI initiatives, experimentation, and proof-of-concepts (PoCs), while gaining experience in scaling AI solutions in production environments.

 

Qualifications

Qualification

Bachelor’s degree in Computer Science, AI, Data Science, Engineering, or related fields

 

Experience
  • 0–3 years of experience in software engineering, AI engineering, or machine learning
  • Basic experience in developing or supporting AI/ML or Generative AI solutions (e.g., academic projects, internships, or early career work)
  • Exposure to cloud platforms or modern application architectures is a plus
  • Experience working in team-based environments and collaborating with cross-functional teams

Certification
  • Relevant certifications in AI, cloud, or data platforms are a plus (e.g., Azure AI, AWS, GCP)
  • Certifications or exposure in MLOps, DevOps, or related areas are advantageous

Skill and Knowledge
  • Basic programming skills in Python and familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
  • Understanding of Generative AI and LLM concepts (e.g., OpenAI, Azure OpenAI, Hugging Face)
  • Basic knowledge of RAG, vector databases, and prompt engineering concepts
  • Familiarity with APIs, microservices, containerization (e.g., Docker), or CI/CD concepts is a plus
  • Exposure to cloud platforms (e.g., Azure, AWS, GCP)
  • Good analytical thinking, problem-solving, and communication skills
  • Basic understanding of Responsible AI, data governance, and security practices

 
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