#104 - AI 软件工程师
#104 - AI Software Engineer
我们正在寻找一名AI软件工程师，负责设计、构建和扩展智能应用、生产级后端服务、代理工作流，以及AI系统与外部工具和平台的集成。该合同职位适合能够快速在软件开发、应用AI实验、集成工作和生产支持方面做出贡献的工程师，同时需平衡性能、可靠性、成本和安全性。
· 有企业经验者优先
主要职责：
· 为内部或面向客户的用例设计、构建和增强AI驱动的应用程序和后端服务。
· 构建和维护能够推理、协调任务并与外部工具和服务集成的AI代理和代理工作流。
· 开发基于MCP的集成和工具接口，使AI系统能够安全地与外部平台、API和业务系统交互。
· 实现提示编排、上下文处理、工具调用、记忆模式和评估工作流，以提高代理的可靠性。
· 与工程、产品和架构团队合作，定义AI代理开发和部署的可扩展模式。
· 将LLM功能集成到软件系统中，同时平衡性能、可靠性、成本和安全性。
· 调查系统问题，提升质量和可观测性，并优化生产环境中的AI工作流效率。
· 参与代码审查、发布支持、实验和生产事件解决。
· 编写技术文档，并为AI工程、代理开发和MCP采用贡献最佳实践。
必备技能
· 4年以上软件工程、后端工程或应用AI工程经验。
· 精通Java和/或Python编程。
· 有构建AI驱动的应用程序或将LLM功能集成到生产系统中的实际经验。
· 有设计或构建AI代理、多步骤编排工作流或使用工具的自动化系统的经验。
· 有使用MCP或类似集成模式连接AI系统与外部工具、API或企业平台的经验。
· 对系统设计、API、分布式系统和生产软件工程基础有深刻理解。
· 熟悉代理系统中的提示设计、上下文管理、评估方法和可靠性模式。
· 在快节奏的交付环境中有效工作的能力。
· 能够独立工作并快速适应新环境。
查看英文原文
We are seeking an AI Software Engineer to design, build, and scale intelligent applications, production-grade backend services, agentic workflows, and integrations between AI systems and external tools and platforms. This contract role is suited for an engineer who can contribute quickly across software development, applied AI experimentation, integration work, and production support while balancing performance, reliability, cost, and safety.
· Enterprise experience strongly preferred
Key Responsibilities:
· Design, build, and enhance AI-powered applications and backend services for internal or customer-facing use cases.
· Build and maintain AI agents and agentic workflows that can reason, orchestrate tasks, and integrate with external tools and services.
· Develop MCP-based integrations and tool interfaces that enable AI systems to interact securely with external platforms, APIs, and business systems.
· Implement prompt orchestration, context handling, tool calling, memory patterns, and evaluation workflows to improve agent reliability.
· Collaborate with engineering, product, and architecture teams to define scalable patterns for AI agent development and deployment.
· Integrate LLM capabilities into software systems while balancing performance, reliability, cost, and safety.
· Investigate system issues, improve quality and observability, and optimize AI workflow efficiency in production environments.
· Participate in code reviews, release support, experimentation, and production incident resolution.
· Create technical documentation and contribute to best practices for AI engineering, agent development, and MCP adoption.
Must-Have Skills
· 4+ years of experience in software engineering, backend engineering, or applied AI engineering.
· Strong programming skills in Java and/or Python.
· Hands-on experience building AI-powered applications or integrating LLM capabilities into production systems.
· Experience designing or building AI agents, multi-step orchestration workflows, or tool-using automation systems.
· Experience with MCP or similar integration patterns for connecting AI systems to external tools, APIs, or enterprise platforms.
· Strong understanding of system design, APIs, distributed systems, and production software engineering fundamentals.
· Familiarity with prompt design, context management, evaluation approaches, and reliability patterns for agent-based systems.
· Proven ability to work effectively in fast-paced delivery environments.
· Delivery-oriented and comfortable operating across development, experimentation, and production support responsibilities.
· Effective at collaborating with cross-functional teams under tight timelines.
· Strong ownership mindset with practical problem-solving skills.
Nice-to-Have Skills
· Experience with multi-agent systems, retrieval-augmented generation, semantic search, or vector-based architectures.
· Familiarity with cloud-native infrastructure, monitoring, and observability for AI services.
· Experience with model evaluation, guardrails, safety patterns, and prompt/version lifecycle management.
· Experience integrating AI solutions with enterprise platforms such as Salesforce, Jira, Slack, or internal developer tools.
· Background in workflow automation, event-driven systems, or backend platforms that support AI-enabled products.
Required Tools & Platforms
· Java and/or Python.
· MCP or similar AI integration patterns for connecting AI systems with external tools, APIs, or platforms.
· LLM and agent-based application environments supporting prompt orchestration, context handling, tool calling, memory, and evaluation.
· APIs and production backend or distributed systems.
Location, Time & Engagement
· Remote contract engagement.
· 100% allocation, approximately 40 hours per week.
· Candidates must be based in APAC or LATAM.
· Candidates must be able to provide working-hours overlap with U.S. Central Time.
· APAC candidates should also be able to provide some overlap with India Standard Time, with availability preferably extending through 11:00 a.m. U.S. Central Time.
· Current engagement end date: March 31, 2027.