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Agentic AI Engineer

💼 Full-time🗓 2026-06-24

Core

Design, build, and orchestrate autonomous AI agents capable of reasoning, planning, and executing complex workflows with minimal human intervention.

Role type

Agentic AI Engineer

Builds

Autonomous agent systems, multi-agent collaboration patterns, and production-ready agent frameworks.

Domain

Artificial Intelligence / Agentic Systems

Deliverable

production ML models

Required skills

Python, prompt engineering, few-shot learning, structured output generation, ReAct, Chain-of-Thought, Tree-of-Thoughts, Plan-and-Solve, vector databases, semantic caching, function calling, API grounding, agentic evaluation, observability, latency optimization, cost optimization, tool development, sandboxed environments

Technologies

Hermes Agent, LangSmith, Arize, Weights & Biases

Responsibilities

Design and implement autonomous agent systems; Build multi-agent collaboration patterns; Implement agentic memory systems; Integrate advanced reasoning techniques; Develop agents capable of dynamic planning and error recovery; Implement tool use and API grounding; Build robust evaluation frameworks; Instrument agents with tracing and logging; Optimize for latency, cost, and reliability; Connect agents to internal and external systems; Develop custom tools and sandboxed environments.

Rewrite
## About the Role We are seeking a forward-thinking Agentic AI Engineer to design, build, and orchestrate autonomous AI agents capable of reasoning, planning, and executing complex workflows. Unlike traditional LLM-based chatbots, our agents interact with dynamic environments, use tools, collaborate with other agents, and operate with minimal human intervention. ## Key Responsibilities ### Agent Architecture & Development - Design and implement autonomous agent systems using frameworks using Hermes Agent. - Build multi-agent collaboration patterns (e.g., orchestrator-workers, debate, hierarchical swarms). - Implement agentic memory systems (short-term, long-term, and episodic memory) using vector databases and semantic caching. ### Reasoning & Planning - Integrate advanced reasoning techniques: ReAct, Chain-of-Thought (CoT), Tree-of-Thoughts (ToT), and Plan-and-Solve. - Develop agents capable of dynamic planning, error recovery, and replanning based on environmental feedback. - Implement tool use (function calling) and API grounding for actions like database queries, API calls, RAG retrieval, and UI automation. ### Production & Evaluation - Build robust evaluation frameworks (agentic eval) to test for task completion, efficiency, and safety—not just lexical similarity. - Instrument agents with tracing, observability, and logging (e.g., LangSmith, Arize, Weights & Biases). - Optimize for latency, cost (token usage), and reliability in production. ### Integration & Tooling - Connect agents to internal and external systems: CRMs, databases, Slack, browsers, REST APIs, and code interpreters. - Develop custom tools and sandboxed environments for agents to execute code or shell commands safely. ## Required Qualifications ### Required Technical Skills - Programming: Expert in Python - Strong understanding of prompt engineering, few-shot learning, and structured output generation (JSON mode, grammars). - Reasoning Patterns: Proven experience implementing agentic patterns (ReAct, Reflexion, Toolformer) in
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