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Staff AI Agent Engineer (Machine Learning)
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Zendesk .
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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 a goal‑oriented, dynamic, and truly conversational system capable of reasoning, planning, and adapting to user needs in real time. 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’re seeking a highly experienced and influential AI Agent Engineer to join our team. In this role, you’ll drive innovation and technical leadership at the forefront of AI technology, focusing on designing, developing, and deploying intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You’ll shape the cognitive architecture for our AI‑powered applications, creating systems that can reason, plan, and execute complex, multi‑step tasks, and guide other engineers.
What You’ll Do (Responsibilities)
Architect, design, and lead the development of robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e.g., LangChain, LlamaIndex), setting technical direction and best practices for engineering teams.
Strategize and oversee the integration of AI agent solutions with existing enterprise systems, databases, and third‑party APIs to create seamless, end‑to‑end workflows across the product, identifying and mitigating architectural risks.
Evaluate and select appropriate foundation models and services from third‑party providers (e.g., OpenAI, Anthropic, Google), analyzing their strengths, weaknesses, and cost‑effectiveness for specific use cases.
Own and drive the entire lifecycle of AI Agent deployment, from concept to production and beyond for large, ambiguous, or highly complex initiatives—collaborating closely with cross‑functional teams, including product leadership and ML scientists.
Troubleshoot, debug, and optimize complex AI systems, ensuring exceptional performance, reliability, and scalability in production environments, and mentoring other engineers in advanced problem‑solving techniques.
Define, establish, and continuously improve platforms and methodologies for evaluating AI agent performance, setting key metrics, driving iterative improvements across the organization, and influencing industry best practices.
Establish and enforce best practices for documentation of development processes, architectural decisions, code, and research findings to ensure comprehensive knowledge sharing and maintainability across the team and wider engineering organization.
Mentor and guide more junior and mid‑level developers, fostering a culture of technical excellence and continuous learning, and contributing to the growth and career development of others.
Core Technical Competencies
Expert in LLM‑Oriented System Design: Architecting and designing complex multi‑step, tool‑using agents (e.g., LangChain, Autogen). Deep understanding of prompt engineering, context management, and LLM behavior quirks (e.g., hallucinations, determinism, temperature effects). Ability to implement advanced reasoning patterns like Chain‑of‑Thought and multi‑agent communication.
Mastery of Tool Integration & APIs: Designing and implementing secure and scalable integrations of agents with external tools, databases, and APIs (e.g., OpenAI, Anthropic) in complex execution environments, often involving novel solutions or significant architectural considerations.
Retrieval‑Augmented Generation (RAG): Designing, building, and optimizing highly performant and robust RAG pipelines with vector databases, chunking, and sophisticated hybrid search techniques.
Leadership in Evaluation & Observability: Defining, implementing LLM evaluation frameworks and comprehensive monitoring for latency, accuracy, and tool usage across production systems, influencing the observability strategy.
Safety & Reliability: Designing and implementing state‑of‑the‑art defenses against prompt injection and robust guardrails (e.g., Rebuff, Guardrails AI) and complex fallback strategies.
Performance Optimization: Deep expertise in managing LLM token budgets and latency through smart model routing, caching (e.g., Redis), and other advanced optimization techniques, identifying and addressing systemic performance bottlenecks.
Planning & Reasoning: Designing and implementing cutting‑edge agents with long‑term memory and highly complex planning capabilities (e.g., ReAct, Tree‑of‑Thought).
Programming & Tooling: Expert in Python, FastAPI, and LLM SDKs; extensive experience and strategic contributions with cloud deployment (AWS/GCP/Azure) and CI/CD for complex AI applications.
Bonus Points (Preferred Qualifications)
Ph.D. / Masters in a relevant field (e.g., Computer Science, AI, Machine Learning, NLP).
Comprehensive 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, LoRA).
The Interview Process
Initial Call with Talent Team – 15 mins
Interview with one member of the Hiring Team – 45 minutes
Take‑home technical challenge
Technical interview with two developers – 1 hour
Final interview with Senior Director and Engineering Manager – 45 minutes
About Zendesk Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and better understand their customers. Zendesk products are easy to use and implement. They give organizations the 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.
Zendesk is an equal‑opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.
By submitting your application, you agree that Zendesk may collect your personal data for recruiting, global organization planning, and related purposes. Zendesk’s Candidate Privacy Notice explains what personal information Zendesk may process, where Zendesk may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Zendesk’s use of your personal information.
The Poland annualized base salary range for this position is zł374,000.00‑zł560,000.00. Salary may vary based on job‑related capabilities, applicable experience, and other factors.
Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience with connection, collaboration, learning, and celebration – while also giving you flexibility to work remotely for part of the week. This role must attend our local office part of the week. The specific in‑office schedule will be determined by the hiring manager.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working enables us to purposefully come together in person, at one of our many Zendesk offices worldwide, to connect, collaborate, and learn while also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you need a reasonable accommodation to submit this application, please send an e‑mail to peopleandplaces@zendesk.com with your specific accommodation request.
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Staff AI Agent Engineer (Machine Learning)
role at
Zendesk .
Get AI‑powered advice on this job and more exclusive features.
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 a goal‑oriented, dynamic, and truly conversational system capable of reasoning, planning, and adapting to user needs in real time. 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’re seeking a highly experienced and influential AI Agent Engineer to join our team. In this role, you’ll drive innovation and technical leadership at the forefront of AI technology, focusing on designing, developing, and deploying intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You’ll shape the cognitive architecture for our AI‑powered applications, creating systems that can reason, plan, and execute complex, multi‑step tasks, and guide other engineers.
What You’ll Do (Responsibilities)
Architect, design, and lead the development of robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e.g., LangChain, LlamaIndex), setting technical direction and best practices for engineering teams.
Strategize and oversee the integration of AI agent solutions with existing enterprise systems, databases, and third‑party APIs to create seamless, end‑to‑end workflows across the product, identifying and mitigating architectural risks.
Evaluate and select appropriate foundation models and services from third‑party providers (e.g., OpenAI, Anthropic, Google), analyzing their strengths, weaknesses, and cost‑effectiveness for specific use cases.
Own and drive the entire lifecycle of AI Agent deployment, from concept to production and beyond for large, ambiguous, or highly complex initiatives—collaborating closely with cross‑functional teams, including product leadership and ML scientists.
Troubleshoot, debug, and optimize complex AI systems, ensuring exceptional performance, reliability, and scalability in production environments, and mentoring other engineers in advanced problem‑solving techniques.
Define, establish, and continuously improve platforms and methodologies for evaluating AI agent performance, setting key metrics, driving iterative improvements across the organization, and influencing industry best practices.
Establish and enforce best practices for documentation of development processes, architectural decisions, code, and research findings to ensure comprehensive knowledge sharing and maintainability across the team and wider engineering organization.
Mentor and guide more junior and mid‑level developers, fostering a culture of technical excellence and continuous learning, and contributing to the growth and career development of others.
Core Technical Competencies
Expert in LLM‑Oriented System Design: Architecting and designing complex multi‑step, tool‑using agents (e.g., LangChain, Autogen). Deep understanding of prompt engineering, context management, and LLM behavior quirks (e.g., hallucinations, determinism, temperature effects). Ability to implement advanced reasoning patterns like Chain‑of‑Thought and multi‑agent communication.
Mastery of Tool Integration & APIs: Designing and implementing secure and scalable integrations of agents with external tools, databases, and APIs (e.g., OpenAI, Anthropic) in complex execution environments, often involving novel solutions or significant architectural considerations.
Retrieval‑Augmented Generation (RAG): Designing, building, and optimizing highly performant and robust RAG pipelines with vector databases, chunking, and sophisticated hybrid search techniques.
Leadership in Evaluation & Observability: Defining, implementing LLM evaluation frameworks and comprehensive monitoring for latency, accuracy, and tool usage across production systems, influencing the observability strategy.
Safety & Reliability: Designing and implementing state‑of‑the‑art defenses against prompt injection and robust guardrails (e.g., Rebuff, Guardrails AI) and complex fallback strategies.
Performance Optimization: Deep expertise in managing LLM token budgets and latency through smart model routing, caching (e.g., Redis), and other advanced optimization techniques, identifying and addressing systemic performance bottlenecks.
Planning & Reasoning: Designing and implementing cutting‑edge agents with long‑term memory and highly complex planning capabilities (e.g., ReAct, Tree‑of‑Thought).
Programming & Tooling: Expert in Python, FastAPI, and LLM SDKs; extensive experience and strategic contributions with cloud deployment (AWS/GCP/Azure) and CI/CD for complex AI applications.
Bonus Points (Preferred Qualifications)
Ph.D. / Masters in a relevant field (e.g., Computer Science, AI, Machine Learning, NLP).
Comprehensive 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, LoRA).
The Interview Process
Initial Call with Talent Team – 15 mins
Interview with one member of the Hiring Team – 45 minutes
Take‑home technical challenge
Technical interview with two developers – 1 hour
Final interview with Senior Director and Engineering Manager – 45 minutes
About Zendesk Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and better understand their customers. Zendesk products are easy to use and implement. They give organizations the 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.
Zendesk is an equal‑opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.
By submitting your application, you agree that Zendesk may collect your personal data for recruiting, global organization planning, and related purposes. Zendesk’s Candidate Privacy Notice explains what personal information Zendesk may process, where Zendesk may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Zendesk’s use of your personal information.
The Poland annualized base salary range for this position is zł374,000.00‑zł560,000.00. Salary may vary based on job‑related capabilities, applicable experience, and other factors.
Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience with connection, collaboration, learning, and celebration – while also giving you flexibility to work remotely for part of the week. This role must attend our local office part of the week. The specific in‑office schedule will be determined by the hiring manager.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working enables us to purposefully come together in person, at one of our many Zendesk offices worldwide, to connect, collaborate, and learn while also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you need a reasonable accommodation to submit this application, please send an e‑mail to peopleandplaces@zendesk.com with your specific accommodation request.
Referrals increase your chances of interviewing at Zendesk by 2x.
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr