Senior AI Agent Engineer (LLM Systems & Autonomous Agents)

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TYPE OF WORK

Full Time

SALARY

700

HOURS PER WEEK

29

DATE UPDATED

Feb 6, 2026

JOB OVERVIEW

We are seeking a highly experienced AI engineer specializing in the design, development, and deployment of LLM-based agents and autonomous AI systems.
This role is not focused on web development, SEO, UI, or general software engineering. It is a deeply technical position for engineers whose core expertise is AI agents, reasoning systems, and large language model orchestration.

Role Overview
You will design and build production-grade AI agents capable of executing complex tasks with minimal supervision. This includes single-agent and multi-agent systems with structured reasoning, memory, tool use, and robust failure handling.

Key Responsibilities
Architect and implement LLM-driven autonomous agents
Build multi-agent systems with coordination, delegation, and feedback loops
Design structured reasoning pipelines (planning, execution, reflection)
Implement long-term and short-ter ---------- mory mechanisms
Integrate tool calling, function execution, and external APIs
Develop Retrieval-Augmented Generation (RAG) systems using vector databases
Debug and mitigate hallucinations, looping behaviors, and reasoning failures
Optimize systems for reliability, latency, cost, and scalability

Required Technical Expertise
Advanced Python engineering (clean, modular, production-ready code)
Deep hands-on experience with OpenAI / GPT-4 / GPT-4.1 / o-series models
Strong understanding of LLM prompting at a system and architectural level
Practical experience with agent frameworks, such as:
LangChain / LangGraph
AutoGen
CrewAI

or equivalent custom implementations

Expertise in embeddings, semantic search, and vector databases:

Pinecone, Weaviate, FAISS, Chroma, or similar

Experience designing and evaluating RAG pipelines

Familiarity with LLM evaluation, observability, and agent debugging

Strongly Preferred Qualifications

Experience deploying AI agents in real-world or production environments

Ability to reason about failure modes, edge cases, and system behavior

Comfort designing AI architectures without reliance on templates or tutorials

Strong understanding of LLM limitations and trade-offs

Ability to clearly explain technical decisions and system designs

What This Role Is Not

Not web development (frontend or backend)

Not SEO, marketing, or automation scripting

Not prompt-only experimentation

Not entry-level or exploratory AI work

Application Requirements

Applicants should submit:

A summary of AI agents or LLM systems they have built

Relevant code samples, repositories, or architecture diagrams

A brief explanation of a challenging AI system problem they encountered and how they solved it

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