AI Architect - 100% Remote

Connect Tech+Talent; Deutschland; Remote; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Connect Tech+Talent is seeking an AI Architect to design autonomous AI systems and multi-agent frameworks. You will lead the architecture of LLM-powered solutions, memory management, and tool integration across cloud platforms.

The role requires 8+ years in software/AI, strong Python skills, and hands-on experience with LangChain and related orchestration frameworks. Remote work from Germany or abroad is supported.

Qualifikationen

• 8+ years in software engineering, ML, or AI architecture.
• 3+ years with LLM-based systems and generative AI.
• Experience designing Agentic AI or multi-agent architectures.
• Proficiency in Python and AI/ML frameworks.
• Hands-on with LLM orchestration frameworks.
• Experience deploying AI workloads on cloud.

Aufgaben

• Design and architect autonomous Agentic AI systems with reasoning.
• Build multi-agent frameworks for complex workflows.
• Define LLM-powered architectures with orchestration, memory management.
• Integrate AI agents with APIs and data platforms.
• Lead AI pipelines, orchestration layers, and evaluation.
• Establish governance, safety, observability, and monitoring.
• Collaborate with product, data science, and engineering teams.
• Guide deployment of AI solutions on Azure, AWS, or GCP.
• Evaluate new autonomous AI technologies and agent frameworks.
• Provide technical leadership to AI/ML engineers.

Kenntnisse

Python programming

LLM architectures

Agentic AI

Multi-agent systems

Cloud platforms

API design

Distributed systems

Team leadership

Ausbildung

Bachelor's or Master's in CS/AI/Data Science

Tools

LangChain

AutoGen

CrewAI

Semantic Kernel

Pinecone

Weaviate

FAISS

Jobbeschreibung

Job Title: AI Architect
Job Location: - 100% Remote
Job type: Long-term Contract

Position Overview

We are seeking an experienced AI Architect with strong expertise in Agentic AI systems to design and implement intelligent, autonomous AI solutions that can reason, plan, and execute complex tasks. The ideal candidate will have deep experience in large language models (LLMs), multi-agent systems, orchestration frameworks, and AI infrastructure, along with the ability to translate business requirements into scalable AI architectures.

This role will involve architecting end-to-end AI solutions, guiding engineering teams, and ensuring reliable deployment of agent-based AI systems across enterprise environments.

Key Responsibilities

• Design and architect Agentic AI systems capable of autonomous reasoning, decision-making, and task execution.
• Build and implement multi-agent frameworks that collaborate to solve complex workflows.
• Define architecture for LLM-powered applications, including prompt orchestration, tool usage, and memory management.
• Integrate AI agents with enterprise systems, APIs, and data platforms.
• Lead the design of AI pipelines, orchestration layers, and evaluation frameworks.
• Establish best practices for AI governance, safety, observability, and monitoring.
• Collaborate with product managers, data scientists, and engineering teams to translate business requirements into AI-driven solutions.
• Guide teams in deploying scalable AI solutions on cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Evaluate and adopt emerging technologies in autonomous AI, reasoning systems, and agent frameworks.
• Provide technical leadership and mentorship to AI/ML engineers.

Required Qualifications

• Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 8+ years of experience in software engineering, machine learning, or AI architecture.
• 3+ years of experience working with LLM-based systems and generative AI solutions.
• Strong experience designing Agentic AI or multi-agent architectures.
• Proficiency with Python and AI/ML frameworks.
• Hands-on experience with LLM orchestration frameworks such as LangChain, AutoGen, CrewAI, Semantic Kernel, or similar.
• Experience working with vector databases (Pinecone, Weaviate, FAISS, etc.).
• Knowledge of RAG architectures, prompt engineering, tool integration, and memory management in AI agents.
• Experience deploying AI workloads in cloud environments (Azure, AWS, or Google Cloud Platform).
• Strong understanding of API design, microservices architecture, and distributed systems.