Software Development Advisor

You have a minimum of 3 years of experience in hands-on software development, focusing on highly technical products. You should have previous experience in Software Development or similar roles at the level of Senior Software Engineer or above. Crafting and tailoring messages for potential customers, including executives, should be one of your strengths. A degree in Computer Science or a related field, or equivalent professional experience, is required for this role. Your skill set should include AI-related experience, with a preference for those who have developed code-based AI agents such as conversational AI agents. Proficiency in React, Typescript, and Go is essential. Previous roles involving direct interaction with end customers to influence software development decisions are beneficial. Engineers working on building AI agents are expected to be self-sufficient at a senior level, comfortable with the standard software development lifecycles, and capable of independently writing code, building components, integrating with APIs, and handling testing/deployment tasks. The AI agent you will be working on is developed programmatically using code, and it is not a no-code/low-code application. All aspects, including setup, permissions, version control, development, testing, and deployment, are managed through extensive coding workflows. Your expertise should include ReactJS and Typescript, proficiency in VCS using Git, and familiarity with other standard engineering workflows. A working understanding of LLMs and writing API integrations in Typescript is also required. You should have a comprehensive understanding of React JS, particularly the core concepts and philosophies of developing with React and front-end frameworks in general. While the Agent SDK has some important distinctions from React, understanding the development and component lifecycles of React will help you adapt to these differences and develop accordingly. Your primary responsibilities as an AI Engineer will include building the agent from scratch based on product requirements. This involves developing the agent, testing various scenarios including knowledge retrieval and support journeys, and writing simulation tests. You may also need to interact directly with clients in a product capacity to ensure that the agent meets their needs and can connect to all necessary APIs and databases. Reviewing live conversations and client feedback using experience manager tools is part of your routine, where you will identify negative conversations, create issues for problematic interactions, receive feedback from clients, and make continuous improvements to enhance the agent's performance and user experience. Regularly checking in, making enhancements, and evaluating metrics are crucial aspects of maintaining the agent's steady state.,