Senior AI/ LLM Engineer

Shinhan Securities Vietnam is looking for an experienced and passionate Senior AI/LLM Engineer to lead the development of state-of-the-art Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) solutions using Large Language Models (LLMs). This role is ideal for individuals who thrive in a fast-paced environment, enjoy solving complex problems, and are motivated to build intelligent systems that deliver real business value. You will play a pivotal role in building and refining language models, designing and maintaining AI pipelines, mentoring junior engineers, and managing the execution of AI projects from inception to delivery.

1. Model Development & Optimization

• Design, develop, fine-tune, and optimize LLMs and NLP models for

applications such as AI chatbots, document understanding, customer

support automation, and intelligent assistants.

• Lead R&D efforts and experimentation to push the boundaries of LLM

capabilities, including implementing new architectures, prompt

engineering, and embedding techniques.

• Apply best practices for LLM deployment, including quantization,

pruning, and evaluation metrics.

2. Data Pipeline and Infrastructure

• Design and implement scalable data pipelines to preprocess, enrich,

and feed training and inference workloads for AI models.

• Build connectors to integrate structured/unstructured data from

databases, APIs, text files, and vector stores (e.g., FAISS, Pinecone).

• Maintain data quality, labeling standards, and reproducibility of

experiments.

3. Deployment & Integration

• Deploy AI models to production environments, ensuring reliability,

security, and high availability.

• Build and maintain APIs or microservices that expose AI capabilities to

other internal teams or customer-facing platforms.

• Monitor deployed models for performance drift, model health, and

retraining needs.

4. Leadership & Collaboration

• Define project scopes, milestones, and timelines for AI initiatives.

• Lead sprint planning, allocate tasks, and prioritize workloads for AI

team members.

• Mentor junior engineers and guide them in solving technical

challenges and upskilling their AI knowledge.

• Coordinate with data scientists, software engineers, business analysts,

and stakeholders to align on requirements and deliverables.

5. Documentation & Presentation

• Document model architectures, experiments, performance

benchmarks, and deployment configurations.

• Deliver technical presentations and demos to internal teams and

executive stakeholders.

• Contribute to internal knowledge base and AI best practices

documentation.

• Minimum 5 years of experience in machine learning, with strong focus on NLP and LLMs.

• Proven experience training and deploying LLMs or working with frameworks like LangChain, LlamaIndex, Hugging Face Transformers.

• Solid understanding of RAG architectures, vector databases, embedding models, and contextual retrieval techniques.

• Strong experience with Python, PyTorch, TensorFlow, and modern MLOps workflows.

• Familiar with API development, Docker/Kubernetes, RESTful services, and CI/CD pipelines.

• Hands-on experience in task and team management, project planning, sprint management, and delivery oversight.

• Excellent communication and presentation skills.

• Good English proficiency (reading/writing/speaking).

• Experience in the financial or securities domain is a plus.