Senior AI Engineer (LLM, RAG, Azure, MLOps)

Top 3 reasons to join us

• Competitive salary + Healthcare insurance package.
• Flexible Working Hours
• 13th month and productivity bonus.

Job description

About the Role

We are looking for a Senior AI Engineer to design, develop, and deploy AI-powered solutions that address complex business challenges. This role requires a strong combination of AI/ML expertise, cloud technologies, MLOps practices, and system design capabilities.

The ideal candidate has experience building AI applications in production environments, contributing to technical architecture decisions, and driving the adoption of modern AI techniques to improve solution quality and scalability.

Key Responsibilities

AI Solution Development

• Design, build, and deploy AI/ML applications and services for production environments.
• Participate in technical design discussions and contribute to architecture decisions for AI-driven systems.
• Develop scalable and maintainable AI solutions aligned with business and technical requirements.
• Evaluate and implement advanced AI techniques to improve system performance and user experience.

Generative AI & Machine Learning

• Design and implement modern AI solutions utilizing technologies and approaches such as:
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Model Context Protocol (MCP)
  • Agentic AI frameworks and workflows
  • Optimize AI applications for performance, accuracy, reliability, and scalability.
  • Collaborate with product and engineering teams to integrate AI capabilities into software products.

Cloud & MLOps

• Build and maintain AI solutions on cloud platforms, preferably Microsoft Azure.
• Develop and manage MLOps pipelines covering model deployment, monitoring, versioning, and continuous improvement.
• Deploy and operate containerized applications using technologies such as Docker and Kubernetes.
• Support production operations and continuously improve system reliability and performance.

Data & System Design

• Work with structured and unstructured data to support AI model development and deployment.
• Design and optimize data pipelines, databases, and data storage solutions for AI workloads.
• Contribute to the design of scalable AI services capable of supporting growing business demands.

Collaboration & Leadership

• Take ownership of assigned initiatives and deliver high-quality solutions.
• Mentor junior engineers and share best practices across the team.
• Collaborate effectively with stakeholders, product teams, and other engineering functions.
• Actively contribute to technical discussions, code reviews, and continuous improvement initiatives.

Your skills and experience

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering, machine learning engineering, or AI development.
• Experience designing scalable and reliable AI services.
• Strong programming skills in Python.
• Strong analytical, problem-solving, and communication skills.
• Demonstrated ownership, accountability, and ability to work independently.
• Proven experience building and deploying AI/ML applications in production environments.
• Experience contributing to system design and technical architecture decisions.
• Strong knowledge of machine learning, generative AI, and modern AI application development.
• Hands-on experience with:
  • Microsoft Azure or other major cloud platforms
  • MLOps tools and practices
  • Docker and container orchestration technologies
  • Model and service deployment
  • Databases and data warehouse solutions

Why you'll love working here

• Competitive salary with 13th‑month bonus, productivity bonus, and annual salary review
• Comprehensive healthcare package, including 24/24 personal accident insurance
• State‑of‑the‑art office environment (gym, shower, basketball & soccer field) with a high‑end laptop provided
• Work hand‑in‑hand with global software teams (Australia, New Zealand, UK, US, Canada…)
• Strong learning culture: paid self‑learning hours, LinkedIn Learning & Pluralsight access, in‑person classes with professional trainers (leadership, soft skills, English…), workshops, technical sharing activities...
• Clear career development with structured onboarding, ongoing training, and a mentorship program
• Flexible working: 5‑day work week and flexible start times
• Free lunch and free parking
• Team bonding through quarterly team‑building events, yearly company outing, and a special 3‑year anniversary trip
• Active social clubs: gym, yoga, football, badminton, swimming…