銳師科技有限公司

What you’ll do: - Own design & development of agent workflows that span email, SMS, social, and contact-management microservices. - Collaborate daily with product managers, data scientists, and fellow engineers to turn marketing use-cases into resilient, observable code. - Mentor junior engineers on evaluation-driven development and modern agent patterns. - Stay current on fast-moving LLM infrastructure (vLLM, LangGraph, MCP) and guide the team in adopting what works. - Shape long-term architecture, ensuring the platform can plug into future AI ecosystems without lock-in. Must-Have Qualifications: - Backend Engineering – 8 + years designing and operating REST / gRPC microservices; expert Python & FastAPI; strong SQL / NoSQL data modelling. - Cloud & DevOps – Hands-on production AWS (Lambda, EKS / Fargate, S3) and infrastructure-as-code with Terraform, CloudFormation, or Helm. - Messaging & Streaming – Practical experience with SQS queues and Kinesis streams for event-driven systems. - AI & Data – Working knowledge of LLMs, prompt engineering, retrieval-augmented generation (RAG), embeddings, and vector databases such as Pinecone, Milvus, or Weaviate. - Kubernetes – Able to author Helm charts, configure autoscaling / HPA, and monitor clusters with Prometheus & Grafana. Preferred Qualifications: - Built or maintained high-throughput, low-latency data systems. - Familiar with MLOps fundamentals (feature stores, model registries) and data-privacy best practices. - Created automated LLM evaluation harnesses using OpenAI Evals, LangChain Bench, MLflow LLM Evaluation, or DeepEval. - Designed red-team and guardrail tests for safety, bias, PII leakage, and prompt-injection resilience with Promptfoo / Guardrails. - Hands-on with LangGraph and other Python agent frameworks (LangChain Agents, CrewAI, AutoGen); designed multi-step agent workflows, branching logic, and reliability guards. - Implemented Model Context Protocol (MCP) servers and adapters to let AI agents securely access external data and tools; defined context schemas, capability negotiation, RBAC, audit logging, and integrated MCP tools via LangGraph / LangChain MCP adapters. - Mentored engineers and contributed to architecture reviews, design documents, and code reviews. You will be a good fit if you: - Enjoy freedom and take responsibility in a remote first environment. (You could choose WFH or in Taipei office) - Are excellent at communicating clearly. (In English of course) - Know how to effectively and efficiently collaborate with people around the world (cross timezones). - Can manage multiple projects concurrently and prioritize effectively. - Leverage open source technologies in a smart and practical way to solve problems while creating maintainable and evolving systems. - Enjoy maintaining a high standard and discussing code quality and design patterns with peers. - Flexible attitude and willingness to frequently move between different teams, software architectures and priorities. - Desire to collaborate with our other product teams to think strategically about how to solve problems. Updated: 2025/06/11

What you’ll do: - Own design & development of agent workflows that span email, SMS, social, and contact-management microservices. - Collaborate daily with product managers, data scientists, and fellow engineers to turn marketing use-cases into resilient, observable code. - Mentor junior engineers on evaluation-driven development and modern agent patterns. - Stay current on fast-moving LLM infrastructure (vLLM, LangGraph, MCP) and guide the team in adopting what works. - Shape long-term architecture, ensuring the platform can plug into future AI ecosystems without lock-in. Must-Have Qualifications: - Backend Engineering – 5 + years designing and operating REST / gRPC microservices; expert Python & FastAPI; strong SQL / NoSQL data modelling. - Cloud & DevOps – Hands-on production AWS (Lambda, EKS / Fargate, S3) and infrastructure-as-code with Terraform, CloudFormation, or Helm. - Messaging & Streaming – Practical experience with SQS queues and Kinesis streams for event-driven systems. - AI & Data – Working knowledge of LLMs, prompt engineering, retrieval-augmented generation (RAG), embeddings, and vector databases such as Pinecone, Milvus, or Weaviate. - Kubernetes – Able to author Helm charts, configure autoscaling / HPA, and monitor clusters with Prometheus & Grafana. Preferred Qualifications: - Built or maintained high-throughput, low-latency data systems. - Familiar with MLOps fundamentals (feature stores, model registries) and data-privacy best practices. - Created automated LLM evaluation harnesses using OpenAI Evals, LangChain Bench, MLflow LLM Evaluation, or DeepEval. - Designed red-team and guardrail tests for safety, bias, PII leakage, and prompt-injection resilience with Promptfoo / Guardrails. - Hands-on with LangGraph and other Python agent frameworks (LangChain Agents, CrewAI, AutoGen); designed multi-step agent workflows, branching logic, and reliability guards. - Implemented Model Context Protocol (MCP) servers and adapters to let AI agents securely access external data and tools; defined context schemas, capability negotiation, RBAC, audit logging, and integrated MCP tools via LangGraph / LangChain MCP adapters. - Mentored engineers and contributed to architecture reviews, design documents, and code reviews. You will be a good fit if you: - Enjoy freedom and take responsibility in a remote first environment. (You could choose WFH or in Taipei office) - Are excellent at communicating clearly. (In English of course) - Know how to effectively and efficiently collaborate with people around the world (cross timezones). - Can manage multiple projects concurrently and prioritize effectively. - Leverage open source technologies in a smart and practical way to solve problems while creating maintainable and evolving systems. - Enjoy maintaining a high standard and discussing code quality and design patterns with peers. - Flexible attitude and willingness to frequently move between different teams, software architectures and priorities. - Desire to collaborate with our other product teams to think strategically about how to solve problems. Updated: 2025/06/11

What you’ll do: - Own the design & development of intuitive, secure, and scalable user interfaces for our AI assistant, supporting real-time interactions across web surfaces. - Collaborate daily with product managers, UX designers, and backend engineers to transform complex agent workflows into elegant, usable frontend experiences. - Lead frontend initiatives and mentor junior engineers in modern web architecture, design patterns, and performance best practices. - Stay current with frontend trends (e.g., SSR, WebSockets) and help guide tech adoption. - Contribute to long-term frontend architecture that scales with our AI ecosystem. Must-Have Qualifications: - Frontend Engineering – 5+ years of experience building and maintaining modern Single Page Applications using JavaScript、React、HTML、CSS. - State Management – Hands-on experience with frontend state libraries like Redux、MobX、Zustand，and managing real-time UI updates. - API Integration – Strong understanding of consuming RESTful APIs、WebSocket、Server-Sent Events，and asynchronous programming patterns. - Testing & Quality – Proficient in frontend testing using Jest、React Testing Library，and comfortable writing maintainable and scalable component code. - Architecture & Deployment – Experience working in CI/CD environments and building secure、performant frontends at scale；familiarity with SSR frameworks like Next.js. Preferred Qualifications: - Experience with real-time rendering and streaming (WebSockets、SSE). - Exposure to AWS or other cloud platforms. - Backend familiarity (Python, microservices) is a plus. - Comfortable discussing frontend scalability、performance、security. You will be a good fit if you: - Enjoy freedom and take responsibility in a remote first environment. (You could choose WFH or in Taipei office) - Are excellent at communicating clearly. (In English of course) - Know how to effectively and efficiently collaborate with people around the world (cross timezones). - Can manage multiple projects concurrently and prioritize effectively. - Leverage open source technologies in a smart and practical way to solve problems while creating maintainable and evolving systems. - Enjoy maintaining a high standard and discussing code quality and design patterns with peers. - Flexible attitude and willingness to frequently move between different teams, software architectures and priorities. - Desire to collaborate with our other product teams to think strategically about how to solve problems. Updated: 2025/08/02