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AI Engineer Agentic Systems Backend

Smilegate Vietnam · Hồ Chí Minh
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Type
Full-time
Work mode
On-site
Level
Staff
Industry
Engineering / Mechanical
Salary
Thương lượng
Location
Quận Bình Thạnh, Hồ Chí Minh, Hồ Chí Minh

Overview

  • Agentic Systems: Design and deploy autonomous AI Agents, building complex workflows including planning, multi-step reasoning, and tool-use/function calling.
  • Data & Retrieval: Build and optimize RAG (Retrieval-Augmented Generation) systems using vector databases and embeddings to provide accurate context for LLMs.
  • AIOps: Establish evaluation pipelines to measure AI quality, minimize hallucinations, and control bias.
  • Resource Optimization: Monitor and optimize latency, token throughput, and operational costs for AI systems.
  • AI Integration: Package AI features into stable APIs for seamless integration into the existing Microservices ecosystem.
  • Core Systems: Design, develop, and manage high-performance backend services, ensuring stability and scalability in production.
  • Feature Development: Maintain existing systems and proactively develop new functionalities based on business requirements.
  • International Collaboration: Work closely with the Korean tech team and stakeholders to align on architectural solutions and application deployment.
  • Code Quality: Apply standard coding practices, ensuring high unit test coverage and optimized debugging processes.
  • Technology Research: Proactively research new technologies, specifically AI infrastructure solutions, to apply to company projects.
  • Experience: 4–6 years of professional experience, including 1–2 years in backend software development and 3–4 years in AI Engineering. Strong proficiency in Python or Java is required. Candidates with hands-on experience in both languages are preferred, using Python for AI/Data applications and Java for core backend services.
  • Architecture: Deep understanding of Microservices, RESTful APIs, and gRPC.
  • Data: Experience with SQL (PostgreSQL, MySQL) or NoSQL (MongoDB, Cassandra).
  • Fundamentals: Mastery of data structures, algorithms, OOP, and common design patterns.
  • LLM Production: Proven experience implementing features using OpenAI, Claude, or open-source models (Llama, Mistral) in production.
  • Frameworks: Proficiency in AI orchestration libraries: LangChain, LangGraph, CrewAI, or AutoGen.
  • Vector Infrastructure: Experience with Vector Databases such as Milvus, Pinecone, Qdrant, or pgvector.
  • Agentic Skills: Solid understanding of Function Calling, Memory management (Long-term/Short-term), and advanced Prompt Engineering (Chain-of-Thought, ReAct).
  • AI Quality: Knowledge of evaluation frameworks (e.g., Ragas, Arize Phoenix, or LangSmith).
  • Experience with high-traffic systems and asynchronous processing.
  • Proficiency in Docker, Kubernetes, and Cloud platforms (AWS/GCP/Azure).
  • Experience with Redis (Caching) and Message Brokers (Kafka or RabbitMQ).
  • Understanding of CI/CD for AI (MLOps).
  • Premium health insurance
  • Safe, ethical, secure, and healthy workplace

Benefits

  • Annual bonus program
  • Personal Development
  • Budget for individual learning & development
  • Work-life balance
  • 14 days of paid annual leave, increasing by 1 day each year
  • Flexible working timeframe
  • Workplace experiences
  • Modern working equipment
  • Well-stocked pantry to relax and recharge.
  • Engagement activities (monthly team bonding, yearly company trip…)
  • Sponsored sports clubs
  • Business trip opportunities to the Korean Headquarters
BonusStock options / ESOP

Summary of facts from the official posting. View original ↗

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