프로젝트 소개
We are seeking an experienced AI/ML Engineer to lead the design and delivery of a production-grade, multi-agent AI platform for enterprise use cases in ITSM and HR. This is a hands-on, technical leadership position that combines deep expertise in large language models (LLMs), retrieval-augmented generation (RAG), hybrid search/retrieval systems, and classical ML approaches such as clustering, anomaly detection, and root-cause analysis.
The successful candidate will own end-to-end architecture — from system design and deployment to performance optimization — partnering closely with Product, Platform, and Security teams to ship secure, reliable, and scalable features for multi-tenant environments.
당신의 의무
As an AI/ML Engineer you will be responsible for:
- Architect and deliver multi-agent orchestration systems with planning, tool-use, agent-to-agent protocols, and memory management, ensuring tenant isolation and governance
- Build high-reliability RAG pipelines including chunking, indexing, hybrid retrieval (BM25 + vector), query rewriting, re-ranking, and grounding with citations
- Develop online inference workflows for LLM and classical ML models, maintaining SLOs for latency, cost, and quality
- Design hybrid enterprise search solutions across structured and unstructured data (documents, tickets, HRIS/ITSM systems, logs, metrics)
- Implement and optimize embeddings, ANN indices, query planning, and feedback-driven re-ranking
- Develop and productionize classical ML models for anomaly detection, clustering, incident classification, and root-cause analysis
- Establish evaluation and safety frameworks, including automated regression testing, red-team testing, and compliance with SOC2/ISO and regional data policies
- Implement guardrails for prompt-injection, PII protection, RBAC, and content filtering
- Mentor engineers, lead design reviews, and collaborate with PMs and Design on roadmap priorities and success metrics
- Partner directly with enterprise clients on architecture reviews, scalability planning, and performance optimization
요구 사항
- 5+ years of experience building production-grade ML/AI systems, with at least 3 years shipping LLM or RAG-based systems at scale
- 3+ years of experience leading distributed, multi-service architectures
- Expert proficiency in Python and Java, with strong foundations in algorithms, data structures, and distributed systems
- Proven delivery experience with RAG architectures using hybrid retrieval, vector databases (FAISS, Milvus, Pinecone, Weaviate), and Elasticsearch/OpenSearch
- Hands-on experience with agent frameworks such as LangGraph, LangChain, AutoGen, or CrewAI
- Proficiency in classical ML techniques including anomaly detection, clustering, and supervised classification
- Familiarity with MLOps and infrastructure tools such as Kubernetes, Docker, MLflow, W&B, Prometheus, and Grafana
- Experience building secure, multi-tenant systems on AWS, Azure, or GCP
- Integration experience with enterprise systems like ServiceNow, Jira, Workday, or SuccessFactors
- Excellent command of English, both written and spoken, sufficient for professional communication in international and technical environments.
- Strong collaboration skills and ability to engage with cross-functional teams (Product, Security, Data Engineering)
Nice to have:
- Experience with graph-based reasoning or topology for root-cause analysis (Neo4j, Neptune)
- Familiarity with retrieval safety, differential privacy, and policy enforcement
- Advanced evaluation knowledge (RAGAS, DeepEval, or LLM-as-judge frameworks)
- Expertise in large-scale vectorization, caching, and cost optimization strategies
- Open-source contributions to LLM, RAG, search, or MLOps frameworks
팀업에 대하여
Team Up에서는 최고의 전문가들이 자국에서 근무하면서도 글로벌 기업에서 원격으로 커리어를 쌓을 수 있도록 지원합니다. 2020년부터 500명이 넘는 인재를 글로벌 기업과 연결하여 국경을 넘나드는 기회를 창출하고 지역 성장을 촉진해 왔습니다. 조지아와 독일의 파트너십으로 시작된 이 파트너십은 이제 연결, 성장, 그리고 더 나은 미래라는 공동의 비전을 바탕으로 7개국으로 확대되었습니다.
Team Up과 함께하는 원격 근무의 이점과 특전
전문적으로 성장하고 존중받고, 보살핌을 받고, 소중하게 여겨진다고 느끼는 데 필요한 모든 것
여러 위치 · 완전 원격