Senior AI Agent Engineer

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 is not 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.

About the Role:

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

What You will do (Responsibilities):

• Design and develop robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e.g., LangChain, LlamaIndex).

• 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., OpenAI, 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 (LangChain, Autogen). Deep understanding of prompt engineering, context management, and LLM behavior quirks (e.g., 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 (OpenAI, 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 (ReAct, Tree-of-Thought).

• Programming & Tooling: Expert in Python, FastAPI, 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, LoRA).