5 дней назад
Lead GenAI / AI-ML SME (Agentic AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead GenAI / AI-ML SME (Agentic AI): Designing and building LLM-powered agents, multi-agent workflows, and RAG capabilities for network anomaly detection and operational intelligence with an accent on agent orchestration, retrieval architecture, and reliable AI-assisted operations. Focus on defining technical strategy, developing evaluation frameworks, guiding solution design, and driving production deployment at scale.
Company
is recruiting for a multinational telecom technology client developing an agentic AI program for network operations.
What you will do
- Shape the solution design and implementation strategy for a network anomaly detection agentic AI program.
- Design and build LLM-powered agents and multi-agent workflows for anomaly detection, triage, root-cause investigation, and operational insight generation.
- Develop RAG capabilities connecting network data, documentation, incident history, and knowledge bases.
- Define technical practices for prompt engineering, tool calling, agent routing, structured outputs, and AI evaluation.
- Collaborate with architects, engineers, data teams, product owners, and client stakeholders to deliver AI capabilities.
- Lead code reviews, architecture discussions, sprint delivery, and knowledge sharing across the GenAI engineering team.
Requirements
- Strong Python software engineering experience with hands-on delivery of GenAI, AI/ML, or LLM-based applications.
- Experience with LangChain, LangGraph, or equivalent agentic AI frameworks.
- Strong knowledge of LLM APIs, tool calling, prompt engineering, structured outputs, streaming, and agent orchestration.
- Experience designing RAG solutions using embeddings, vector search, hybrid retrieval, re-ranking, and answer generation.
- Technical SME capabilities with strong communication, consulting, solution design, and stakeholder-facing skills.
- Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment.
Nice to have
- Experience with network operations, anomaly detection, incident analysis, telecommunications, or enterprise operations.
- AWS, Azure, or Google Cloud AI/ML certification.
- Certification or training in artificial intelligence, machine learning, data engineering, cloud architecture, or software engineering.
- Network, telecom, or operations-focused certifications.
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