Job Description
Build and develop AI products that can automatically plan, make decisions, and take actions, and can be deployed at large scale in real-world environments, including next-generation AI systems such as:
AI Agents (Autonomous Agents)
LLM-powered Applications
Multi-agent Workflow Systems
AI-driven Backend Services
Intelligent Automation Platforms
Responsibilities:
Design and develop backend systems integrated with AI/LLM agents.
Build agentic workflows, including planning, tool use, memory, and execution.
Develop AI services as microservices using FastAPI, Flask, Django, Java, or Go.
Integrate AI models into product systems through REST or gRPC APIs.
Deploy production-ready AI systems using Docker and Kubernetes.
Optimize inference performance in terms of latency, throughput, and cost.
Work with large-scale data and high-traffic systems, especially in finance, banking, and securities.
Research and apply advanced techniques such as RAG, function calling, multi-agent systems, and reinforcement learning agents.
Ensure AI systems meet requirements for security, safety, and scalability.
Job requirements
Bachelor's degree in Information Technology, Computer Science,
Software Engineering, Information Systems, Automation, Telecommunications/Electronics, or related fields.
Hands-on experience working as a Backend Engineer in a company or on large-scale projects.
Proficient in at least one backend programming language; Python, Go, and C/C++ are preferred.
Experience designing systems based on Microservices Architecture.
Strong knowledge of at least one database management system, such as PostgreSQL, MongoDB, etc.
Solid understanding of API design (RESTful/gRPC), security, and system performance optimization.
Experience with:LLM Agents (GPT, Gemini, Claude, etc.)
LangChain / LangGraph / ADK / AutoGen
RAG pipelines
Vector Databases (Milvus, pgvector, etc.)
Tool-use Agents (Function Calling)
Memory, planning, and multi-step reasoning systems
Proficient in Git/GitFlow.
Experience with Docker, Kubernetes, etc.
Preferred Qualifications:
Experience in finance, banking, or securities domains.
Understanding of AI Safety, Guardrails, and Model Monitoring.
Experience optimizing AI systems for cost efficiency in production.
For Junior/
Fresher candidates: preference will be given to those with Excellent/Distinction academic performance, high GPA, prizes in academic or professional competitions, provincial/city-level gifted student awards or above, or published research in international conferences/journals. (Candidates should clearly include GPA and awards in their CVs.)
Knowledge of data processing techniques in NLP, Computer Vision, Speech, and Video Understanding.
Understanding of model architectures such as CNN, RNN, Transformer, Attention, GNN, etc.
Application Instructions:
Apply directly on the MB Bank recruitment page on [protected info]
MB Bank requires applicants to provide the following details:
Personal information: Full name, Date of birth, Gender
Contact phone number and Email
Education level, Graduating school
Work experience
3 to 5 standout skills
Why should you apply directly via [protected info]
Your application will be assessed quickly.
Applicants should regularly check their email and phone to ensure they don't miss the interview schedule.