[IT Dept.] Senior AI Engineer

At MB Life, we believe that AI is the core driver of breakthroughs in the insurance industry and a key enabler for optimizing the way we work. As a Senior AI/ML Engineer, you will be at the forefront of exploring, evaluating, and applying cutting-edge AI technologies from the open-source community and leading global providers to solve real-world business challenges.
Your mission is not to build everything from scratch, but to stand on the shoulders of giants—leveraging the power of pre-trained models, cloud-based AI platforms, and open-source solutions to deliver value quickly, from enhancing customer experiences to automating and accelerating internal software development processes.

Key Responsibilities

1. Research, Experimentation, and Integration of AI Solutions:

• Proactively research and evaluate AI models, libraries (e.g., Hugging Face, LangChain), and cloud-based AI services (AWS/GCP/Azure) to identify the most suitable technologies for each use case.
• Rapidly build Proof-of-Concept (PoC) prototypes to validate the feasibility and effectiveness of AI solutions before large-scale deployment.
• Design system architectures and directly integrate AI solutions into the company’s existing systems (Java backend, Flutter/Dart applications) via APIs.

2. Process Automation and Optimization with AI:

• Analyze the Software Development Lifecycle (SDLC) and propose AI-powered tools (e.g., AI Copilots, AIOps, AI for Testing) to improve DORA metrics (accelerating deployment, reducing failure rates).
• Develop internal AI systems using Retrieval-Augmented Generation (RAG) techniques to optimize access and utilization of the company’s knowledge base (Jira, Confluence, business documentation).

3. AI Operations and Governance (MLOps):

• Deploy AI models/services as containers (Docker) on Kubernetes platforms.
• Establish CI/CD pipelines to automate packaging and deployment of AI services.
• Build monitoring systems to track performance, costs, and effectiveness of AI services in production; detect and mitigate model drift early.
• Implement guardrails to ensure AI solutions are safe, secure, and ethically responsible.

• A Bachelor’s degree in Mathematics, Statistics, Software Engineering, Computer Science, or a related fiel
• Experience: 
  • ​Minimum of 5 years in Software Engineering, with at least 2 years of hands-on experience in applying and deploying AI/ML solutions.
  • Proven expertise in integrating pre-trained AI models (e.g., Hugging Face) and/or third-party AI services (OpenAI, Google AI, AWS AI) into real-world products.
  • Experience in building and deploying applications on cloud platforms (AWS, GCP, Azure).
  • Understanding of software development process optimization and DORA metrics is a significant advantage.
• Technical Skills:
  • ​Proficiency in Python and AI/ML-related libraries.
  • Strong experience in API development and integration (REST, gRPC).
  • Solid knowledge of Docker and a basic understanding of Kubernetes.
  • Hands-on experience with at least one cloud provider (AWS/GCP/Azure).