Artificial Intelligence Engineer

AI Engineer (LLMs & Agentic Workflows)

Role Overview

We’re looking for an AI Engineer with hands-on experience in building applications

powered by Large Language Models (LLMs) and emerging agentic workflows. You’ll

design, implement, and optimize intelligent systems that go beyond simple prompt-

response interactions—integrating tools, memory, and decision-making into production-

grade solutions.

This role sits at the intersection of software engineering, applied AI, and product

development. You’ll work closely with product managers, data scientists, and software

engineers to deliver scalable, reliable AI-driven features.

Key Responsibilities

 Design and build applications using LLMs for real-world use cases

 Develop and maintain agentic workflows (multi-step reasoning, tool use,

planning, memory handling)

 Implement prompt engineering strategies and evaluation pipelines

 Integrate LLMs with APIs, databases, vector stores, and external tools

 Ensure reliability, observability, and performance of AI systems in production

 Run experiments, benchmark models, and iterate based on measurable

outcomes

 Stay up to date with rapidly evolving LLM and agent frameworks

Required Qualifications

 2–5 years of experience in software engineering, machine learning, or applied AI

 Strong programming skills in Python (experience with async, APIs, and data

pipelines)

 Practical experience working with LLMs in production or advanced prototypes

 Familiarity with frameworks such as LangChain, LangGraph, or similar

 Understanding of prompt engineering, tokenization, and model limitations

 Experience integrating APIs, microservices, and cloud platforms

 Solid grasp of software engineering best practices (testing, versioning, CI/CD)

Preferred Qualifications

 Understanding of security and safety considerations in AI systems

 Experience designing agent-based systems (tool use, planning, orchestration)

 Familiarity with vector databases

 Experience optimizing latency, cost, and reliability of LLM systems

 Exposure to text-to-speech, speech-to-text, and voice orchestration techniques

would be an advantage

 Strong debugging and problem-solving skills in non-deterministic systems

Izvor: https://www.linkedin.com/jobs/view/4470839426/

Nivo: mid level