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招 AI 工程师（LLM&Agents） Role: AI Engineer (LLM & Agents) Location: Silicon Valley/Beijing/Shanghai
grace202 · Jan 27 · 1976 viewsThis topic created in 93 days ago, the information mentioned may be changed or developed.
Role Overview
As an AI Algorithm Engineer, you will design and build the core AI systems powering Brix’s
recruiting OS—from LLM-based reasoning and agents, to matching algorithms and workflow
automation.
You will be responsible for:
——Building agentic AI systems capable of planning, tool use, memory, and autonomous task
execution
——Designing multi-agent coordination and workflow orchestration
——Developing candidate–role matching, skill extraction, trait inference, and ranking algorithms —
—Improving LLM performance (prompting, fine-tuning, RAG, model routing)
——Shipping production-quality AI features with rapid iteration cycles
——Owning model quality, reliability, and performance metrics
Who You Are
We're looking for AI-native, builder-type engineers who thrive in ambiguity.
l Experience architecting long-context, multi-step, or persistent agents
l Knowledge of agent planning architectures (ReAct, Reflexion, Tree-of-Thought,
Graph-of-Thought, RA-As-A-Graph, AutoGen, CrewAI, Swarm)
l Ability to design robust state machines for agent behavior
l Experience with long-term memory, episodic memory, vector databases
l Memory compression / summarization strategies
l Schema design for agent state
l Experience creating eval suites (MMLU-style, behavioral tests, golden datasets)
l Familiarity with output scoring + model routing
l Human-in-the-loop feedback pipelines
Familiarity with:
l Strong backend engineering (Python, FastAPI, Node, or Go)
l Kafka / event queues / async workers
l Docker, Kubernetes, CI/CD
Nice to have:
l Familiar with AI hardware architecture design, cloud architecture, AWS certificate is a strong
plus.
l Research ability to implement new agent architectures from papers.
Critical differentiator (please highlight this)
You have built AI agents yourself—either: as a successful side project / indie project, OR as a
startup founder / technical owner who designed and implemented agent systems end-to-end
Nice to Have: Hands-on model tuning, AI system building, open-source work, startup experience,
curiosity for recruiting / org design / people systems—or willingness to rapidly learn
Why Join Us
l Ship AI systems used by Google, TikTok, Luma, and fast-scaling startups
l Use technology to genuinely change how people work and grow
l Strong resources （$10M+ funding, $50M+ revenue trajectory ）
l A small, exceptional team you help build
If you believe AI should elevate people, not replace them—and you want to build the
[email protected] & [email protected]
As an AI Algorithm Engineer, you will design and build the core AI systems powering Brix’s
recruiting OS—from LLM-based reasoning and agents, to matching algorithms and workflow
automation.
You will be responsible for:
——Building agentic AI systems capable of planning, tool use, memory, and autonomous task
execution
——Designing multi-agent coordination and workflow orchestration
——Developing candidate–role matching, skill extraction, trait inference, and ranking algorithms —
—Improving LLM performance (prompting, fine-tuning, RAG, model routing)
——Shipping production-quality AI features with rapid iteration cycles
——Owning model quality, reliability, and performance metrics
Who You Are
We're looking for AI-native, builder-type engineers who thrive in ambiguity.
l Experience architecting long-context, multi-step, or persistent agents
l Knowledge of agent planning architectures (ReAct, Reflexion, Tree-of-Thought,
Graph-of-Thought, RA-As-A-Graph, AutoGen, CrewAI, Swarm)
l Ability to design robust state machines for agent behavior
l Experience with long-term memory, episodic memory, vector databases
l Memory compression / summarization strategies
l Schema design for agent state
l Experience creating eval suites (MMLU-style, behavioral tests, golden datasets)
l Familiarity with output scoring + model routing
l Human-in-the-loop feedback pipelines
Familiarity with:
l Strong backend engineering (Python, FastAPI, Node, or Go)
l Kafka / event queues / async workers
l Docker, Kubernetes, CI/CD
Nice to have:
l Familiar with AI hardware architecture design, cloud architecture, AWS certificate is a strong
plus.
l Research ability to implement new agent architectures from papers.
Critical differentiator (please highlight this)
You have built AI agents yourself—either: as a successful side project / indie project, OR as a
startup founder / technical owner who designed and implemented agent systems end-to-end
Nice to Have: Hands-on model tuning, AI system building, open-source work, startup experience,
curiosity for recruiting / org design / people systems—or willingness to rapidly learn
Why Join Us
l Ship AI systems used by Google, TikTok, Luma, and fast-scaling startups
l Use technology to genuinely change how people work and grow
l Strong resources （$10M+ funding, $50M+ revenue trajectory ）
l A small, exceptional team you help build
If you believe AI should elevate people, not replace them—and you want to build the
[email protected] & [email protected]
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1
Ghrhrrv146 Jan 28
Could you introduce the compensation?
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2
Ghrhrrv146 Jan 28
@Ghrhrrv146 fix: explain the compensation package
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