AI Engineer at TechX Corporation

, , Vietnam -

Full Time

Start Date

Immediate

Expiry Date

28 Sep, 26

Salary

0.0

Posted On

30 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

RAG, LangChain, LlamaIndex, Vector Databases, Prompt Engineering, NLP, GenAI, Python, PyTorch, TensorFlow, REST API, Microservices, vLLM, Azure AI, Vertex AI, AWS Bedrock

Industry

IT Services and IT Consulting

Description

Company Overview: At TechX, we are pioneers in delivering cutting-edge solutions that empower businesses to thrive in today’s digital landscape. With a strong focus on Cloud Transformation (AWS), Data Modernization, and Generative AI, we bring unparalleled expertise to drive innovation, efficiency, and growth for our clients. We specialize in banking and financial services, retail, manufacturing, and transportation, delivering impactful solutions that address industry-specific challenges and significant market shifts. Together, we’ll build a future where innovation knows no limits. Job Overview: We are looking for an AI Engineer focused on Retrieval-Augmented Generation (RAG) and knowledge pipelines. You will build the ingestion, indexing, and retrieval layer that lets our AI agents answer with cited, traceable, domain-specific knowledge. This layer is foundational to the accuracy and trust of our AI products. Key Responsibilities: Design and implement RAG pipelines: document ingestion, chunking, embedding, indexing, retrieval, and citation. Build domain knowledge packs with source citation and traceable answers. Implement data classification, access control, and quality checks for sensitive / regulated corpora. Tune retrieval quality — embeddings, re-ranking, hybrid search — and support evaluation of answer accuracy and grounding. Integrate the knowledge layer with the agent runtime and orchestration APIs. Collaborate with Solution Engineers and customers to onboard real document corpora into demo- and production-quality packs. Key Requirements: Minimum 2+ years of experience in GenAI or NLP. Strong hands-on experience with RAG and Agentic frameworks (LangChain, LlamaIndex), and a solid understanding of RAG, Agentic, and DeepSearch. Experience integrating with vector databases including Qdrant, ChromaDB, OpenSearch, and Pinecone. Understanding of the Model Context Protocol (MCP). Familiar with AI platforms such as Azure AI, Vertex AI; bonus if familiar with AWS Bedrock / SageMaker and chatbot development. Familiar with the Hugging Face transformers library, PyTorch, and TensorFlow. Strong foundation in Computer Science. Experience implementing REST API, gRPC, WebSocket, microservices, and web technologies. Experience with vLLM, llama.cpp, and GGUF-type models. Understanding of and proficiency in prompt engineering. What We Offer: Innovative Environment: A dynamic and collaborative work environment where innovation is encouraged. Professional Growth: Opportunities for professional growth and development through continuous learning and exposure to cutting-edge technologies. Competitive Package: Competitive salary and benefits package Impactful Work: The chance to work on cutting-edge projects with industry-leading clients, making a tangible impact on their business success. Apply now! Due to the high volume of applicants, only shortlisted candidates will be contacted. We apologize for this inconvenience!

Responsibilities

Design and implement RAG pipelines for document ingestion, indexing, and retrieval to enable AI agents with traceable knowledge. Integrate the knowledge layer with agent runtimes and collaborate with customers to onboard production-quality document corpora.