AI Engineer
AI/Artificial Intelligence Engineering
Salary
Location
Job Overview And Responsibility
RAG Development - Design, build, and optimize end-to-end RAG pipelines (ingestion → indexing → retrieval → reranking → generation). - Integrate and tune vector databases (Pinecone, Weaviate, Milvus, Chroma, etc.). - Improve chunking strategies, embedding quality, and similarity search performance. - Build evaluation pipelines for RAG (precision/recall, context relevance, response quality). Agentic AI / AI Agents - Develop AI Agents using frameworks like LangGraph, AutoGen, or LlamaIndex Agents. - Design multi-agent workflows (planner → executor → evaluator). - Implement tool/function calling, serverless integrations, and dynamic reasoning workflows. Model Context Protocol (MCP) - Design and implement MCP servers exposing tools, APIs, and datasets to LLMs. - Integrate MCP into application stack (frontend ↔ backend ↔ LLM). - Build custom MCP tools (database connectors, internal API tools, scraping tools, etc.). System Architecture & MLOps - Build and maintain inference infrastructure (Docker, Kubernetes, GPU servers). - Implement logging, monitoring, and observability for RAG/Agent pipelines. - Optimize model serving cost and performance (quantization, vLLM, batching, TensorRT, etc.).
Required Skills and Experience
- Minimum of 3–5 years of experience in advanced analytics, machine learning/deep learning model development, and/or applying AI/GenAI to practical business problems. - Strong proficiency in Python (FastAPI / Flask). NodeJS is a plus. - Practical experience building production-level RAG systems. - Deep understanding of LLMs, embeddings, vector databases, and reranking. - Hands-on experience with RAG/Agent frameworks: LangChain, LlamaIndex, LangGraph, etc. - Familiarity with Docker, Linux, and basic DevOps. - Strong debugging and system thinking skills. - Strong communication and presentation skills, with the ability to clearly explain AI/LLM/RAG concepts to both technical and non-technical audiences. - Ability to deliver AI solution presentations and product demos, effectively explaining system architecture, workflows, and business value. - Fluent oral and written English - Teaching and mentoring mindset, capable of supporting junior engineers and cross-functional teams (PMs, BAs, Sales, Clients) in understanding and applying AI solutions.
Why Candidate should apply this position
🎯Flexible working regime and health care: - Flexible timekeeping (from 8:00 - 9:00 to 17:30 - 18:30) - Minimum 14 paid leaves per annum for all employees after probation - 01-day remote work per month - A flexitime allowance of 90-180 minutes per month for employees - 01 hour paid leave per day for women having children under 12 months - Social insurance, health insurance, unemployment insurance and MIC care insurance 🎯Transparent and fair benefits: - Saturday & Sunday OFF, Overtime pay is 150%, 200%, 300% as per labor law; - 13th-month salary, Performance Bonus - Bonus Policy: Public holidays (2/9, 30/4, 1/5, 1/1,...); Personal Performances; Excellent Team; Performance bonus in Token of the project;.. - Men’s Day, Women’s Day, Children’s Day, Mid-Autumn Festival and other benefits under the provisions of the company 🎯Dynamic environment and open culture: COMPENSATION & BENEFITS - Year-end party, sports day, yearly company trip and quarterly team building,...with a generous budget - Socialize with colleagues through monthly Happy Hour - Monthly allowance when joining clubs: Soccer, Swimming, Yoga, Music,... - Nice & modern working space with young, dynamic & friendly colleagues and free coffee, tea, drinks,... - Flat, open and sharing culture with friendly management team; outsourcing company with product mindset 🎯Strong learning culture: - Free training courses for technical and soft skills (presentation skills, communication skills, foreign language courses,...) - Account to log in to our online learning system, which contains thousands of valuable lectures (LMS) - Participate in workshops, seminars, tech talk,... with sharing from experts inside and outside the company - Working opportunities with technical gurus who built and operated world-class applications with millions of users.
Preferred skills and experiences
- Candidates with experience in client training, presales activities, solution presentations, or creating AI educational materials (slides, documentation, demos) are preferred.
Report to
Client
Interview process
English phonescreen (online) -> 2 technical round
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