{"id":3855,"date":"2026-10-15T22:35:03","date_gmt":"2026-10-15T15:35:03","guid":{"rendered":"https:\/\/trivita.ai\/?p=3855"},"modified":"2026-10-15T22:35:04","modified_gmt":"2026-10-15T15:35:04","slug":"tuyen-dung-senior-agentic-ai-engineer","status":"publish","type":"post","link":"https:\/\/trivita.ai\/en\/tuyen-dung-senior-agentic-ai-engineer\/","title":{"rendered":"Hiring SENIOR AGENTIC AI ENGINEER"},"content":{"rendered":"<ul class=\"wp-block-list\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<\/ul>\n\n\n\n\n\n<ul class=\"wp-block-list\">\n\n\n\n\n\n\n\n\n\n\n\n<\/ul>\n\n\n\n\n\n<ul class=\"wp-block-list\">\n\n\n\n\n\n\n\n\n\n<\/ul>\n\n\n\n\n\n<ul class=\"wp-block-list\">\n\n\n\n\n\n\n\n\n\n<\/ul>\n\n\n\n\n\n<ul class=\"wp-block-list\">\n\n\n\n<\/ul>\n\n\n\n<p>Trivita AI is hiring a Senior Agentic AI Engineer to build production AI agents, Graph RAG, knowledge graphs, retrieval systems, and evaluation frameworks.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Job description<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Design and build production-grade AI agents capable of multi-step reasoning, planning, tool use, and workflow execution.<\/li>\n\n\n\n<li>Architect knowledge-intensive AI systems using Knowledge Graphs, Graph RAG, and hybrid retrieval.<\/li>\n\n\n\n<li>Develop search and retrieval pipelines, including indexing, query understanding, ranking, reranking, and context construction.<\/li>\n\n\n\n<li>Build evaluation frameworks and benchmarks to measure agent success, retrieval quality, latency, and cost.<\/li>\n\n\n\n<li>Run rigorous experiments, analyze failure cases, and systematically improve end-to-end agent performance.<\/li>\n\n\n\n<li>Research and implement relevant techniques from recent papers, validating their effectiveness through controlled experiments.<\/li>\n\n\n\n<li>Develop robust agent architectures with state management, memory, tool orchestration, and failure recovery.<\/li>\n\n\n\n<li>Collaborate with backend and infrastructure engineers to deploy, monitor, and continuously improve AI systems in production.<\/li>\n\n\n\n<li>Own complex technical problems from research and architecture through implementation, evaluation, and production rollout.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Requirements<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong hands-on experience building and deploying AI agents or advanced LLM-powered systems beyond basic API wrappers and prompt chains.<\/li>\n\n\n\n<li>Deep practical understanding of information retrieval, search systems, or knowledge-intensive AI architectures.<\/li>\n\n\n\n<li>Experience designing evaluation frameworks, building benchmarks, analyzing failure cases, and iterating based on measurable results.<\/li>\n\n\n\n<li>Strong Python engineering skills and the ability to deliver maintainable, production-ready AI systems.<\/li>\n\n\n\n<li>Ability to read research papers critically, reproduce relevant methods, and validate whether they deliver measurable improvements.<\/li>\n\n\n\n<li>Experience making architectural trade-offs involving agent reliability, reasoning quality, latency, and inference cost.<\/li>\n\n\n\n<li>Strong ownership and problem-solving skills, with the ability to drive ambiguous AI challenges independently.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Technical skills<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Agentic Systems:<\/strong> Tool calling, planning, multi-step execution, agent orchestration, state management, and workflow reliability.<\/li>\n\n\n\n<li><strong>Retrieval &amp; Search:<\/strong> Hybrid search, dense and sparse retrieval, reranking, query expansion, and retrieval evaluation.<\/li>\n\n\n\n<li><strong>Knowledge Systems:<\/strong> Knowledge Graphs, Graph RAG, entity resolution, graph traversal, and structured context retrieval.<\/li>\n\n\n\n<li><strong>Evaluation:<\/strong> Task-specific benchmarks, end-to-end agent evaluation, tracing, error analysis, and systematic experimentation.<\/li>\n\n\n\n<li><strong>Agent Memory:<\/strong> Short- and long-term memory, context management, memory retrieval, and knowledge updating.<\/li>\n\n\n\n<li><strong>Production AI:<\/strong> Latency and cost optimization, observability, failure recovery, concurrency, and scalable serving.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Preferred qualifications<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Experience building agents for specialized domains such as Medicine, Law, or other knowledge-intensive industries.<\/li>\n\n\n\n<li>Experience building evaluation frameworks or benchmark datasets from scratch.<\/li>\n\n\n\n<li>Familiarity with LangGraph, LlamaIndex, DSPy, DeepEval, Ragas, or equivalent technologies.<\/li>\n\n\n\n<li>Experience with Neo4j, Qdrant, Elasticsearch, or similar knowledge and retrieval infrastructure.<\/li>\n\n\n\n<li>Experience with multi-agent systems, agent memory architectures, or reinforcement learning for agent optimization.<\/li>\n\n\n\n<li>Research publications, open-source AI contributions, or demonstrated technical work beyond standard framework usage.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Contact information<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Address: No. 01, Street 104, Quarter 3, Binh Trung Ward, Ho Chi Minh City<\/li>\n\n\n\n<li>Phone: 0937519182<\/li>\n\n\n\n<li>Email: hr@trivita.ai \/ le.vu@trivita.ai<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Trivita AI is hiring a Senior Agentic AI Engineer to build production AI agents, Graph RAG, knowledge graphs, retrieval systems, and evaluation frameworks. Job description Requirements Technical skills Preferred qualifications Contact information<\/p>","protected":false},"author":1,"featured_media":3852,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-3855","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tuyen-dung"],"_links":{"self":[{"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/posts\/3855","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/comments?post=3855"}],"version-history":[{"count":1,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/posts\/3855\/revisions"}],"predecessor-version":[{"id":3856,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/posts\/3855\/revisions\/3856"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/media\/3852"}],"wp:attachment":[{"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/media?parent=3855"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/categories?post=3855"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/trivita.ai\/en\/wp-json\/wp\/v2\/tags?post=3855"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}