高级AI工程师（生成式AI与智能系统）
Senior AI Engineer (Generative AI & Agentic Systems)
Developer Role and Responsibilities :
在这个职位中，你将设计、构建和部署生产级的生成式AI和代理式AI解决方案，以自动化复杂的业务流程并增强企业工作流。你将参与整个交付生命周期，从解决方案设计和提示/代理架构到开发、评估和部署，并与自动化、数据和平台团队紧密合作。职责包括LLM驱动的应用程序的动手开发、与利益相关者的解决方案设计，以及对初级开发人员在生成式AI最佳实践方面的指导。你将与我们获奖的商业和技术专家及领导者团队密切合作。
Key Responsibilities :
- 设计和开发LLM驱动的应用程序，包括RAG（检索增强生成）管道、代理工作流和多步骤自主代理，使用LangChain和LangGraph等框架
- 使用向量数据库（如ChromaDB）和语义搜索构建和优化检索架构，使LLM响应基于企业数据
- 应用提示工程技巧，提高基于LLM的解决方案在托管（OpenAI API、Claude Code、Claude）和离线/自托管模型中的准确性、可靠性和成本效率
- 作为客户和内部利益相关者在AI解决方案设计、可行性及交付时间表方面的技术联系人
- 通过REST API、webhooks和云服务（AWS Lambda、Azure）将生成式AI解决方案集成到现有企业系统中，确保安全、可扩展的部署
- 通过引入AI驱动的决策和自我修复功能，扩展或现代化现有的RPA/自动化资产（如Blue Prism、基于代码的自动化框架）
- 协调AI解决方案交付物（解决方案设计文档、评估报告、部署操作手册）的开发、审查和文档编写
- 使用Git、GitHub Actions、Jenkins和Splunk等工具建立AI应用的CI/CD和监控实践
- 识别与模型性能、数据质量和安全性相关的风险；在开发、测试或部署期间缓解障碍
Qualifications and Skills
- 计算机科学、信息技术、工程或同等教育和经验的学士学位
- 至少5–8年的软件开发经验，其中至少2年有构建生成式AI或代理式AI应用程序的经验
- 熟练掌握Python、React、Kubernetes、Stripe等技术栈
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Developer Role and Responsibilities :
In this role, you will design, build, and deploy production-grade Generative AI and Agentic AI solutions that automate complex business processes and augment enterprise workflows. You will work across the full delivery lifecycle, from solution design and prompt/agent architecture through development, evaluation, and deployment, partnering closely with automation, data, and platform teams. Responsibilities will include hands-on development of LLM-powered applications, technical solutioning with stakeholders, and mentoring of junior developers on GenAI best practices. You will work closely with our team of award-winning business and technical specialists and leaders.
Key Responsibilities :
- Design and develop LLM-powered applications, including RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and multi-step autonomous agents using frameworks such as LangChain and LangGraph
- Build and optimize retrieval architectures using vector databases (e.g., ChromaDB) and semantic search to ground LLM responses in enterprise data.
- Apply prompt engineering techniques to improve accuracy, reliability, and cost-efficiency of LLM-based solutions across both hosted (OpenAI API, Claude Code, Claude) and offline/self-hosted models.
- Serve as a technical point of contact for clients and internal stakeholders on AI solution design, feasibility, and delivery timelines.
- Integrate GenAI solutions with existing enterprise systems via REST APIs, webhooks, and cloud services (AWS Lambda, Azure) to ensure secure, scalable deployment.
- Extend or modernize existing RPA/automation assets (e.g., Blue Prism, code-based automation frameworks) by incorporating AI-driven decisioning and self-healing capabilities.
- Coordinate the development, review, and documentation of AI solution deliverables (solution design documents, evaluation reports, deployment runbooks).
- Establish CI/CD and monitoring practices for AI applications using tools such as Git, GitHub Actions, Jenkins, and Splunk.
- Identify risks related to model performance, data quality, and security; mitigate roadblocks during development, testing, or deployment.
Qualifications and Skills
- Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent education and experience.
- Minimum 5–8 years of software development experience, including at least 2 years building Generative AI or Agentic AI applications in production.
- Hands-on experience with LLM application frameworks (LangChain, LangGraph) and LLM APIs (OpenAI API or equivalent).
- Strong understanding of RAG architectures, prompt engineering, and vector databases (e.g., ChromaDB or similar).
- Proficiency in Python; working knowledge of C#, JavaScript, and SQL.
- Experience with cloud platforms and services (AWS Lambda, Amazon DynamoDB, Azure) and REST API integration.
- Experience with DevOps tooling (Git/GitHub, GitHub Actions, Jenkins) and application monitoring (e.g., Splunk).
- Background in RPA or process automation (e.g., Blue Prism, UiPath, or Automation Anywhere) is a strong plus.
- Understanding of IT delivery methodologies (Agile, Lean, ITIL).
- Excellent planning, problem-solving, and technical leadership skills.
Desired characteristics in candidates :
- Self-motivated and able to take initiative with minimal supervision.
- Senior AI Developer (Generative AI & Agentic Systems)
- Effective communicator, able to translate technical AI concepts for non-technical stakeholders.
- Highly organized and methodical, while comfortable adapting to changing requirements.
- Strong analytical and problem-solving skills, with a bias toward experimentation and iteration.
- High emotional intelligence and cross-functional collaboration skills.
- Demonstrated willingness to dive into implementation details to guide projects to completion.
- Team-oriented, with an interest in mentoring and knowledge-sharing.
- Curious and committed to staying current with the fast-evolving GenAI/Agentic AI landscape.
Compensation and start dates
- Hiring now for immediate start
- Salary: Competitive base and bonus determined by level and experience
WonderBotz is an Equal Employment Opportunity employer.
Originally posted on Himalayas