AI Engineer – AI Agent

Overview

Viettel Cyber ​​Security (VCS) is a leading cybersecurity company specializing in protecting digital infrastructure globally through in-depth research and analysis of security solutions. With 100% self-developed technology, VCS provides an advanced cybersecurity solution ecosystem, protecting governments, financial institutions, large enterprises, and SMEs from increasingly sophisticated threats in the digital age.

VCS has received international recognition, including the Pwn2Own Championship 2023 & 2024, consistently ranking in the Top 5 globally, discovering over 400 zero-day vulnerabilities, and numerous prestigious awards, most notably the Gold Award – Best Cybersecurity Company in Asia.

We are looking for one Experienced-level and one Senior-level candidate to join the project; the requirements and job descriptions for each level are outlined below.

Responsibilities

As an Experienced AI Engineer (AI Agent), you will take ownership of building reliable AI agents for assigned use cases, with a focus on basic evaluation, monitoring, and production quality.

1. Develop AI Agents for Product Use Cases

• Develop AI agents for use cases such as conversational Q&A, data retrieval (text-to-SQL / Data Platform querying), compliance review, data analysis, and insight generation — as well as new use cases emerging along the product roadmap.
• Build and optimize RAG pipelines, including chunking, embedding, vector search, reranking, and citation-based responses to ground agents in internal data and documentation and reduce hallucinations.
• Apply prompt engineering, function/tool calling, and structured output; integrate LLMs with APIs, databases, and internal tools, with MCP (Model Context Protocol) as a preferred standard.
• Test and validate AI agent accuracy, continuously optimize agent performance, and ensure safe operation in production environments.

1. Production Deployment & Quality Assurance

Implement basic evaluation (eval), monitoring, and tracing for AI agents; apply existing guardrails such as out-of-scope query handling and authorization enforcement, while optimizing token usage and latency according to product requirements.

Translate business requirements into AI agent workflows with clear error handling and fallback mechanisms; collaborate with Analytics, Backend/Data, and Product teams to bring AI capabilities into production.

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As a Senior AI Engineer (AI Agent), you will design AI agent systems that maximize the value of a unified and interconnected data platform. You will define technical standards for multi-agent systems, semantic layers, and release-gating evaluation, ensuring that the platform is reliable, secure, and scalable for sensitive cybersecurity data.

As use cases continuously expand with user needs and the product roadmap, you will design a general-purpose and reusable agent platform — including shared tools/MCP, semantic layers, and evaluation frameworks — that enables rapid development of new use cases while maintaining quality. You will also provide technical leadership and mentorship to the AI engineering team.

1. AI Agent Architecture & System Development

• Design end-to-end AI agent architectures for use cases such as conversational Q&A, Data Platform querying (text-to-SQL / semantic layer), compliance review, data analysis, and new use cases driven by the product roadmap.
• Design multi-agent workflows with agent handoffs, fallback mechanisms, and human-in-the-loop controls for irreversible or high-impact actions.
• Build a semantic layer with consistent definitions of metrics, entities, and data lineage to improve agent reasoning and query generation across the unified data platform; standardize reusable tools/MCP services across the platform.
• Build and evolve production-grade RAG systems, including hybrid search, reranking, retrieval quality optimization, and citation-based responses; establish data-driven mechanisms for continuously measuring and improving retrieval quality.

1. Quality, Reliability & Security

• Build an evaluation framework that gates deployment, including golden datasets, model-graded evaluation, and regression suites integrated into CI pipelines; establish end-to-end observability and tracing.
• Optimize LLM usage, latency, and cost; design monitoring and usage-management mechanisms across AI agents.
• Design AI agents with protection against prompt injection, data leakage, unauthorized access, and other AI-specific security risks.
• Make architectural decisions around scalability and maintainability; evaluate and select technologies aligned with the system architecture and product requirements.

1. Technical Leadership & Collaboration

• Provide technical leadership through mentoring Middle/Junior engineers, conducting code reviews, and collaborating with Product, Data, and DevOps teams to improve the team’s engineering capabilities and delivery efficiency.

Qualifications

Experienced AI Engineer (AI Agent)

• 3+ years of experience in software development and/or AI/ML, including hands-on experience building products powered by LLMs or AI agents.
• Strong proficiency in Python and solid software engineering fundamentals, including Git, REST APIs, modular design, and unit testing.
• Hands-on experience integrating LLM APIs, including prompt engineering, function/tool calling, and structured output.
• Practical experience building RAG systems, including embeddings, vector databases such as Qdrant, Milvus, or pgvector, retrieval, and citation.
• At least one hands-on Agentic AI project using frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
• Experience working with tabular and text data.
• Bachelor’s degree in Computer Science, Information Technology, Cybersecurity, or a related field.

Bonus Points

• Experience with MCP (Model Context Protocol) and/or text-to-SQL / semantic layers.
• Basic LLMOps experience, including evaluation frameworks such as RAGAS, DeepEval, or promptfoo, and observability tools such as Langfuse or LangSmith.
• Knowledge of system architecture, including SQL/NoSQL databases, containers, message queues, and big data technologies such as Spark and notebooks.
• Strong systems thinking and a product-oriented mindset.

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Senior Data Engineer

• 5+ years of experience in AI/ML and/or software engineering, including 2–3 years of hands-on experience building production-grade AI agents and RAG systems.
• Strong proficiency in Python and production-grade software engineering practices, including system design, testing, and CI/CD.
• Hands-on experience building and deploying production-grade RAG systems, including hybrid search, reranking, and citation, as well as multi-agent systems using commonly adopted frameworks.
• Strong LLMOps experience, including designing and using evaluation frameworks such as RAGAS, DeepEval, or promptfoo; observability/tracing; prompt versioning; and cost/latency management.
• Practical experience with AI guardrails and security, including hallucination mitigation, prompt injection protection, and access control for sensitive data.
• Strong understanding of system architecture, including SQL/NoSQL databases, microservices, containers/Kubernetes, and message queues.
• Bachelor’s degree in Computer Science, Information Technology, Cybersecurity, or a related field..

Bonus Points

• Experience with MCP, including designing and implementing MCP servers that expose internal data and services.
• Experience deploying self-hosted/open-source LLMs such as Llama, Qwen, or DeepSeek, including model serving with vLLM/Ollama, quantization, and fine-tuning with LoRA/PEFT.
• Experience with big data technologies such as Hadoop, Spark, Trino/Presto, and notebooks, with hands-on experience handling large-scale datasets.
• General knowledge of the cybersecurity domain.
• Experience mentoring engineers and providing technical direction aligned with product goals

Benefits & perks

• Competitive annual total income package offers
• Regular salary review every March

• Premium health and personal accident insurance
• Annual periodic health check-ups
• Special support program for female employees during maternity leave.

• Awards recognize outstanding capabilities and timely contributions.
• 100% sponsorship for advanced international professional certifications for each position (if luck isn’t on your side, don’t worry, VCS will support 50% of the exam costs), and exceptional rewards for employees who achieve international professional certifications.
• Continuous investment in the latest and most up-to-date learning materials on the market in the field of information security from leading global suppliers and reputable institutions.
• 100% of employees are provided with Elearning accounts from Udemy – learn anytime, anywhere.
• Free participation in professional knowledge sharing programs and seminars from leading speakers in the country and internationally.

• Opportunity to work with diverse domestic and international clients.
• Work in a Class A office – Landmark 72 building with a green space complex and dedicated areas for gym and entertainment (billiards, PES, café, reading).
• Relax for 30 minutes each day with Happy Hours (4 PM – 4:30 PM).
• Sports activities: Swimming, Pickleball, Billiards, Poker, PES, etc.

• Twelve (12) days of annual leave according to the Labor Law, three (3) vacation days and one (1) traditional holiday on December 22nd of Viettel.

• Personal birthday celebrations: gifts and birthday cakes provided by the company.
• Participation in company events: quarterly team-building activities, monthly birthday celebrations, year-end parties, company retreats, holidays such as March 8th and October 20th (female employees get half a day off), the group’s anniversary on June 1st, etc.
• Showing care and concern for employees’ parents and children on special occasions.