Senior Ai Agent Architect For Next‑gen Conversational Systems

Senior Ai Agent Architect For Next‑gen Conversational Systems
Lisboa
Lisboa, Lisboa, Portugal

Job Description

The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting‐edge AI Agent system that pushes the boundaries of conversational AI. Gen3 is not a typical chatbot;



it is a goal‐oriented, dynamic, and truly conversational system capable of reasoning, planning, and adapting to user needs in real tap‐time. By leveraging a multi‐agent architecture and advanced language models, Gen3 delivers personalized and engaging user experiences, moving beyond scripted interactions to handle complex tasks and "off‐script" inquiries with ease.

About The Role

We are seeking a passionate and experienced AI Agent Engineer to join our team. In this role, you will innovate at the forefront of AI technology, designing, developing, and deploying intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You will build the cognitive architecture for our AI‐powered applications, creating systems that can reason, plan, and execute complex multi‐step tasks. You will communicate complex technical concepts to both technical and non‐technical stakeholders, including those outside your immediate team.

Responsibilities

- Design and develop robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e. G. , Lang
Chain, Llama
Index).

- Integrate AI agent solutions with existing enterprise systems, databases, and third‐party APIs to create seamless end‐to‐end workflows.

- Evaluate and select appropriate foundation models and services from third‐party providers (e. G. , Open
AI, Anthropic, Google), analyzing their strengths, weaknesses, and cost‐effectiveness for specific use cases.

- Drive the entire lifecycle of AI Agent deployment—collaborate closely with cross‐functional teams, including product managers, ML scientists, and software engineers, to understand user needs and deliver effective, high‐impact agent solutions.

- Troubleshoot, debug, and optimize complex AI systems to ensure optimal performance, reliability, and scalability in production environments.

- Establish and improve platforms for evaluating AI agent performance, defining key metrics to measure success and guide iteration.

- Document development processes, architectural decisions, code, and research findings to ensure knowledge sharing and maintainability across the team.

Core Technical Competencies

- LLM‐Oriented System Design: Designing multi‐step, tool‐using agents (Lang
Chain, Autogen), deep understanding of prompt engineering, context management, and LLM behavior quirks (hallucinations, determinism, temperature effects);



implementing advanced reasoning patterns like Chain‐of‐Thought and multi‐agent communication.

- Tool Integration & APIs: Integrating agents with external tools, databases, and APIs (Open
AI, Anthropic) in secure execution environments.

- Retrieval‐Augmented Generation (RAG): Building and optimizing RAG pipelines with vector databases, advanced chunking, and hybrid search.

- Evaluation & Observability: Implementing LLM evaluation frameworks and monitoring for latency, accuracy, and tool usage.

- Safety & Reliability: Defending against prompt injection and implementing guardrails (Rebuff, Guardrails AI) and fallback strategies.

- Performance Optimization: Managing LLM token budgets and latency through smart model routing and caching (Redis).

- Planning & Reasoning: Designing agents with long‐term memory and complex planning capabilities (Re
Act, Tree‐of‐Thought).

- Programming & Tooling: Expert in Python, Fast
API, and LLM SDKs;



experience with cloud deployment (AWS/GCP/Azure) and CI/CD for AI applications.

Bonus Points (Preferred Qualifications)

- Ph. D / Masters in a relevant field (e. G. , Computer Science, AI, Machine Learning, NLP).

- Deep understanding of foundational ML concepts (attention, embeddings, transfer learning).

- Experience adapting academic research into production‐ready code.

- Familiarity with fine‐tuning techniques (e. G. , PEFT, Lo
RA).

Interview Process

- Initial Call with Talent Team – 15 minutes

- Interview with one member of the Hiring Team – 45 minutes

- Take‐home technical challenge

- Technical interview with two developers – 1 hour

- Final interview with 2 of the following: CTO or Engineering Manager/Director – 45 minutes

About Zendesk

Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and to better understand their customers. Zendesk products are easy to use and implement, giving organisations flexibility to move quickly, focus on innovation, and scale with their growth. More than 100, 000 paid customer accounts in over 150 countries and territories use Zendesk products. Based in San Francisco, Zendesk has operations in the United States, Europe, Asia, Australia and South America.

EEO and Disability Accommodations

Zendesk is an equal‐opportunity employer, committed to fostering diversity and inclusion. All hiring decisions are made without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre‐employment testing, or otherwise participate in the employee selection process, please send an email to peopleandplaces@zendesk.com with your specific accommodation request.

Job Details

- Seniority level: Mid‐Senior level

- Employment type: Full‐time

- Job function: Engineering and Information Technology

- Industries: Software Development

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