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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer II - **Company:** Uber - **Location:** Sunnyvale, CA, United States (Remote available) - **Salary:** $171,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Amazon Alexa, Amazon Web Services, Microsoft Azure, Cloud Computing, Software Quality, Code Review, Data Structures, Distributed Systems, Python (Programming Language), Machine Learning, Scala (Programming Language), Data Logging, Scripting, Google Cloud, Chatbots, Large Language Models, Software Troubleshooting, Generative AI, Git, Solid Principles, Apache Kafka, Restful APIs, Software Version Control, Golang, Programming Languages, Microservices - **Published:** June 23, 2026 - **Apply:** https://www.dice.com/job-detail/bb14078b-5807-467a-89cf-b71f29f4dc70 ## About the Role 1\\. Bachelors Degree, or above, in Comp Science or related field 2\\. Scalable system architecture design 3\\. Production-quality services, deployment, monitoring, and reliability. 4\\. Microservice designs, gRPC or REST API development 5\\. Ability to decompose complex business problems into clean, extensible, performant services and systems 6\\. Logging, monitoring, performance troubleshooting and tuning experience 7\\. Excellent problem-solving skills and the ability to work in a collaborative team environment 8\\. Comfortable in navigating multi-disciplinary teams with respect 9\\. Focus on code quality in terms of coverage, code reviews 10\\. Excellent technical writing skills to communicate design, requirements, flows, architecture 11\\. Fluent in one of these programming languages: Golang, Scala, Java, 12\\. Comfortable in one of these scripting languages: Javascript, python 13\\. Solid understanding of algorithms, data structures, and software design principles. 14\\. Experience with version control systems such as Git. Preferred Qualifications 1\\. Experience in machine learning, GenAI, or LLM technologies. 2\\. Experience with building conversational assistants 3\\. Dialog management systems like Google Dialogflow, Amazon Alexa 4\\. Familiarity with large scale distributed systems like Kafka and cloud platforms like AWS, Google Cloud Platform, or Azure. 5\\. Familiarity with communication channel interfaces eg: WhatsApp, SMS, slack ## Description The Conversational Assistants team brings together Uber's products, state of the art cognitive technologies and Uber's engineering infrastructure to deliver automated conversational assistants a.k.a chatbots to provide enhanced customer experience. Our chatbots are capable of interacting with customers, performing cognitive analysis of customer interactions in real time and responding and interacting automatically with the customers. Our automated assistants are built on dialog management frameworks, Uber's support logic, natural language understanding models and customer communication data to deliver automated support experience that reduces burden on human agents and provides faster response to the customers. We constantly thrive on providing the next generation of customer assistants which are a result of Uber's big bold bets. As a result we are building the next generation chatbots leveraging GenAI models to provide more personalized, empathetic, human-like conversations that are also compliant with Uber's business policies . What You'll Do We are seeking a strong and passionate software engineer with experience in building chatbots. You will be responsible for creating scalable, reliable, manageable chatbots that deliver on conversational requirements at Uber by bringing together LLM prompts and Assistant building platforms at Uber. You will be owning customer facing chatbots that impact the support experience of millions of customers. You will also be leading the NLP based chatbot to GenAI based chatbot migrations as well as augmenting the existing GenAI chatbots with new features and capabilities. Your responsibility will include identifying required changes across Uber's engineering ecosystem, collaborating with engineering teams, driving consensus, implementing extensible, maintainable changes required to build state-of-the-art support experiences. We are looking for someone who has passion for designing and driving large projects from inception to production. The right person will work with stakeholders, product managers, scientists, partner engineering teams to gather requirements and translate them into a platform feature. 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