AI Agent Engineer (Machine Learning Engineer)
Role details
Job location
Tech stack
Job description
The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting-edge AI Agent system that's pushing the boundaries of conversational AI. Gen3 isn't your typical chatbot; it's a goal-oriented, dynamic, and truly conversational system capable of reasoning, planning, and adapting to user needs in real-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., We're seeking a passionate AI Agent Engineer to join our team. In this role, you'll contribute to innovating at the forefront of AI technology, focusing on developing and refining intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You'll be a key player in implementing and improving the cognitive architecture for our AI-powered applications, creating systems that can reason, plan, and execute complex, multi-step tasks. You'll primarily focus on defined project scopes and tasks , working under the guidance of more senior team members., * Contribute to the design and development of robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e.g., LangChain, LlamaIndex).
- Support the evaluation and selection of appropriate foundation models and services from third-party providers (e.g., OpenAI, Anthropic, Google), contributing to the analysis of their strengths, weaknesses, and cost-effectiveness for specific use cases.
- Participate in the lifecycle of AI Agent deployment-collaborate closely with your immediate team, including product managers and software engineers, to understand user needs for the features you're building.
- Troubleshoot and debug AI systems to ensure optimal performance and reliability in production environments for assigned components.
- Document development processes, code, and findings to ensure knowledge sharing and maintainability within the team.
Requirements
Do you have experience in Zendesk?, Do you have a Master's degree?, * Familiarity with LLM-Oriented System Design: Understanding of multi-step, tool-using agents (e.g., LangChain, Autogen). Basic understanding of prompt engineering, context management, and LLM behavior (e.g., hallucinations).
- Tool Integration & APIs: Ability to integrate agents with external tools, databases, and APIs (e.g., OpenAI, Anthropic) in secure execution environments.
- Retrieval-Augmented Generation (RAG): Understanding of RAG pipelines with vector databases.
- Evaluation & Observability: Basic understanding of LLM evaluation frameworks and monitoring for latency and accuracy.
- Safety & Reliability: Awareness of prompt injection and basic concepts of implementing guardrails and fallback strategies.
- Performance Optimization: Basic understanding of managing LLM token budgets and latency.
- Planning & Reasoning: Familiarity with concepts of agents with long-term memory and planning capabilities.
- Programming & Tooling: Proficient in Python (Fast API) and LLM SDKs;
Bonus Points (Preferred Qualifications):
- Bachelor's or Master's in a relevant field (e.g., Computer Science, AI, Machine Learning, NLP).
- Understanding of foundational ML concepts (attention, embeddings, transfer learning).