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The Agentic Tribe is building Gen3, a goal-oriented AI agent system that uses a multi-agent architecture and large language models to provide real-time reasoning, planning, and adaptable conversations beyond scripted interactions. The role of AI Agent Engineer focuses on developing and refining autonomous agents and cognitive architectures that enable reasoning, planning, and execution of complex tasks, under guidance from senior team members. Responsibilities include designing robust, stateful AI agents with Python and frameworks like LangChain and LlamaIndex; evaluating foundation models from providers; collaborating with product managers and engineers; debugging production systems; and documenting processes. Core competencies cover LLM-oriented system design, tool integration and APIs, retrieval-augmented generation, evaluation and observability, safety and reliability, performance optimization, planning and reasoning, and Python tooling, with bonus qualifications including relevant degrees and foundational ML concepts. The interview process spans an initial talent call, a team interview, a take-home technical challenge, technical interviews with developers, and a final interview, and Zendesk notes its global presence, commitment to diversity and inclusion, candidate privacy, potential AI-based screening, and accommodations for applicants with disabilities.

Zendesk is seeking a Staff Machine Learning Engineer to level up its full-text search platform and AI-powered products, including retrieval-augmented-generation bots, used by over 145,000 global brands. The role involves delivering AI capabilities at scale with the latest LLM tech, collaborating with Product Management, ML scientists, and engineers to define features, mentoring juniors, maintaining service stability, writing clean code, and contributing to technical design, while tackling challenges like expanding RAG use cases, hybrid search, ranking, indexing speed/cost, and multi-channel retrieval. Basic qualifications include proficiency in Python or Ruby, solid software architecture knowledge, a collaborative growth mindset, ability to work independently, experience building scalable applications, and the ability to form hypotheses and analyze experiments. Preferred qualifications include designing and optimizing ML-based search (Elasticsearch), AWS cloud experience, and event-driven architectures using Kafka. The tech stack features Python/Ruby, PyTorch, AWS, data stores such as MySQL, Redis, S3, Elasticsearch, Kafka, and Snowflake, with Kubernetes and Docker for deployment and Datadog/Sentry for monitoring, and Zendesk offers growth opportunities, ownership at scale, specialization options, a hybrid work policy, and a commitment to equal opportunity and inclusion with accommodations for applicants.