Original listing text, shown exactly as published by the company.
Your day-to-day
- Build and maintain conversational AI agents using Google Dialogflow CX and Vertex AI Agent Builder, contributing to flows, fulfilment logic and agent configurations - always with the customer journey in mind.
- Support the development of agentic workflows – learning how to design multi-step, tool-using agents that can reason and act across systems to resolve customer queries.
- Work with the Google Agent Development Kit (ADK) to assist in building, testing and iterating on agent capabilities under the guidance of more senior engineers.
- Analyse conversational data and real customer interaction patterns to understand how users engage with our agents, surfacing insights that inform improvements to the customer experience.
- Contribute to the testing and quality assurance of conversational flows and agentic pipelines, identifying and resolving errors or unexpected behaviour.
- Assist in the analysis of conversational data and performance metrics to support continuous improvement of the user experience.
- Collaborate with Conversation Designers, product managers and engineers to ensure technical implementations match the intended design and business goals.
- Participate in team ceremonies including stand-ups, retrospectives and planning sessions, communicating your progress and raising blockers clearly.
- Stay curious about developments in agentic AI, LLMs and the broader conversational AI landscape, sharing learnings with the team through show and tells or internal channels.
Your skillset
We’re looking for someone who brings enthusiasm, a genuine interest in conversational and agentic AI technology, and the willingness to grow. You don’t need to have all the answers but you should be eager to find them.
- Conversational AI Core: Foundational understanding of conversational AI concepts - virtual agents (intents, entities, dialogue management, fulfillment) through to LLM-driven agentic approaches.
- Platform Exposure: Experience building virtual agents on conversational platforms (e.g., Google Dialogflow CX, Vertex AI Agent Builder, Amazon Lex, Rasa).
- Software Engineering: Strong programming proficiency in Python or TypeScript or other programming language, backed by solid software engineering and infrastructure development practices.
- Advanced LLM Orchestration: Experience designing LLM applications beyond basic APIs, including retrieval-augmented generation (RAG) pipelines, orchestration logic, and tool/agent workflows.
- API Integration: Strong awareness of REST APIs and webhooks to effectively connect AI agents with backend systems and external tools.
- Cloud & DevOps: Familiarity with cloud deployment environments (preferably Google Cloud Platform) and CI/CD practices for AI workflows.
Desirable
- Experience with the Google Agent Development Kit (ADK), LangChain, or similar multi-agent orchestration frameworks.
- Practical familiarity with vector databases, hybrid search techniques, and advanced chunking strategies for optimizing RAG systems.
- Knowledge of or previous experience within the travel sector or fast-paced B2C e-commerce environments.
- Familiarity with version control tools (Git) and working effectively within an agile team environment.
The interview journey
- TA screening - 30 mins
- 1st stage video interview with Lead Conversational AI Engineer - 1 hour
- Take-home engineering task
- Final stage with Director of Business IT & AI Operations and senior stakeholders - 1 hour
