Senior AI Engineer (Agentic Systems)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior AI Engineer (Agentic Systems): Designing and shipping production-grade LLM agents for a workforce orchestration platform with an accent on multi-agent orchestration and semantic retrieval. Focus on building reliable agent workflows, implementing RAG pipelines over knowledge graphs, and ensuring enterprise-grade reliability and safety.
Location: Israel
Company
is an AI-native system of action for workforce orchestration, providing an agentic HR platform for large enterprises.
What you will do
- Design and build multi-agent systems including intent routing, planning, and tool coordination across specialized agents.
- Implement RAG pipelines over structured and unstructured workforce data grounded in a knowledge graph.
- Integrate LLMs with function calling and protocols like MCP to provide controlled access to HCM systems and business logic.
- Develop evaluation harnesses, guardrails, and safety/bias checks to ensure reliable and policy-compliant agent behavior.
- Deploy model-agnostic agents across providers (Anthropic, Google, IBM watsonx) into Microsoft Teams, Slack, and Copilot.
- Optimize agents for latency, cost, and reliability at an enterprise scale.
Requirements
- 5+ years of experience building production software.
- Proven track record of shipping LLM agents to production environments.
- Hands-on experience with agent orchestration frameworks such as LangGraph, LangChain, AutoGen, or CrewAI.
- Strong proficiency in Python and solid software engineering fundamentals.
- Expertise in prompt engineering paired with systematic, measurable evaluation of LLM outputs.
- Experience deploying, monitoring, and maintaining AI in production using cloud, CI/CD, and observability tools.
Nice to have
- 2+ years of hands-on experience with LLMs and generative AI.
- Practical experience with RAG, embeddings, and vector databases (e.g., pgvector, Pinecone).
- Experience with MCP, agent memory, and planning/reasoning patterns.
- Background in HR tech, people data, or skills ontologies.
- Experience with knowledge graphs or Graph ML (GNNs).
- Knowledge of Responsible AI, bias evaluation, and AI governance.
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