ABOUT ONE MOUNT
One Mount is Vietnam's largest technological ecosystem that creates solutions along the entire value chain, starting with retail, distribution, real estate, and financial services. Our mission is to build Vietnam's most trusted ecosystem, empowering all people and businesses to realize their full potential at the intersection of technology and humanity.
We are seeking a forward-thinking AI Agent Engineer to join our team. In this role, you will build autonomous, enterprise-grade multi-agent systems capable of complex reasoning and task execution.
Work Location: HN
Level: Middle/Senior
MAIN RESPONSIBILITIES
- Own the entire lifecycle of agentic systems, from architectural design and prompt engineering to evaluation and deployment.
- Develop high-performance REST APIs (using FastAPI or Node.js) with robust handling of timeouts, retry logic, rate limiting, and error management.
- Integrate and manage LLMs (OpenAI/Anthropic or self-hosted models) optimizing parameters like temperature, top-k, top-p and token limits
- Implement advanced agent patterns (ReAct, Plan-and-Solve, Reflection) and equip agents with the ability to use external tools effectively.
- Build comprehensive evaluation pipelines and define metrics to measure agent reliability, accuracy, and safety.
- Ensure system observability by implementing tracing and debugging workflows for complex agent steps.
- Deep knowledge of Recommendation Systems (RecSys), spanning from foundational techniques (Collaborative Filtering, Content-based Filtering, Matrix Factorization, Factorization Machines) to state-of-the-art approaches.
- Hands-on experience with modern RecSys paradigms, including:
- Graph-based Recommenders for modeling user–item–context relationships.
- Sequential / Session-based Recommenders for capturing user behavior over time.
- Generative Recommendation models and their integration with foundation models.
- Ability to bridge RecSys with LLM/Agent systems - LLM-augmented recommendation, conversational recommenders, agentic personalization workflows, and embedding-based retrieval at scale.
- Familiarity with offline/online evaluation methodologies for RecSys (NDCG, Recall@K, MRR, AUC, A/B testing, counterfactual evaluation) and large-scale serving challenges (candidate generation, ranking, re-ranking).
REQUIRED EXPERIENCE AND SKILLS
- Bachelor’s degree in Computer Science, Data Science or a related field.
- Strong software engineering foundation with a solid understanding of algorithms, data structures, and system design principles.
- Hands-on experience with Docker and comfortable working in Linux environments.
- Proficiency in Python (primary) and familiarity with TypeScript (secondary).
- Mastery of modern agent frameworks such as LangGraph, Google ADK, CrewAI, AutoGen, or OpenAI Agents SDK.
- Deep experience implementing agentic workflows, multi-agent collaboration architectures, and advanced prompting techniques.
- Hands-on experience with Vector Databases and hybrid search strategies for RAG implementation.
- Solid understanding of Deep Learning concepts, specifically Transformer architectures and attention mechanisms.
- Experience with observability and evaluation tools (e.g., LangSmith, Arize) to trace, debug, and run experiments on agent performance.
- Practical experience with LLM fine-tuning is a strong bonus.
- Ability to manage context effectively, implementing short-term and long-term memory strategies for agents.
- Experience in asynchronous systems (Kafka, RabbitMQ, Redis PubSub) or real-time communication (WebSocket, gRPC) is preferred.
- Experience in building specific AI Voice Assistants/Call Centers, or implementing advanced strategies for hallucination reduction and LLM caching is preferred.
- Engineer advanced RAG systems with complex context window management and long-term memory persistence strategies.
- Optimize production performance, focusing on latency, cost efficiency, and throughput of LLM calls.
- Architect and build scalable, stateful multi-agent systems where specialized agents collaborate to solve complex enterprise problems.
BENEFIT AND PERKS
Salary & Allowances
- 13-month salary with annual performance bonus, project incentives, sales incentives (based on position)
- Lunch allowance: 730.000 VND/month
- Special occasion bonus: 3.000.000 - 5.000.000 VND/year
- Annual leaves: Up to 20 days/year (based on levels)
- Health: Social insurance, premium health insurance, yearly health check
- Laptop, screen and other needed facilities/ accounts/ tools for work
Career Growth
- Yearly salary review and promotion
- Diverse career path: Management or Expert and functions rotation opportunity
- Free learning sources in Udemy, Coursera, O'relly platforms; internal workshop, certification sponsorship, and exclusive mentoring from C-levels
- Recognition and awards at team and organizational levels.
Working Environment
- Open & collaborative working space foster both individual focus and teamwork activities
- Young, dynamic, and collaborative working atmosphere
- Unwind zones: gaming, table tennis, yoga, gyms, bath rooms, sleep corner.
- Quarterly/yearly teambuilding & engaged internal events.
