Full-Stack Developer

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 135.000; Vollzeit

Zusammenfassung

Jobtailor is seeking an experienced AI systems engineer in Germany to design and implement multi-agent architectures with real-time dashboards and cross-channel integrations. You will work across the stack from embeddings to live monitoring, ensuring secure, scalable, and observable AI services.

Role requires hands-on with Docker, Kubernetes, and various LLM APIs, plus strong back-end and front-end skills in TypeScript/Node.js and React/Next.js. German work location preferred.

Qualifikationen

• Proven experience with multi-agent AI systems and architectures.
• 2+ years of experience with RAG/embeddings at scale.
• 2+ years with several LLM APIs (Claude, OpenAI, Grok, DeepSeek, Kimi, Gemini).
• Experience in sentiment analysis and NLP.
• 2+ years with MCP (Model Context Protocol).
• 3+ years back-end with TypeScript/Node.js (NestJS).
• 3+ years front-end with TypeScript (React/Next.js).
• Experience with RESTful APIs and WebSockets for real-time comms.
• Knowledge of relational and NoSQL databases.
• Experience with WhatsApp Business API or Twilio-like solutions.
• Experience building bots for Discord and/or Telegram.
• Knowledge of human-in-the-loop design for AI systems.
• Hands-on with Docker and Kubernetes.
• Knowledge of Linux servers and production deployments.
• Good Git practices and web app security awareness.
• Experience with real-time dashboards and monitoring.

Aufgaben

• Design and implement AI agent hierarchies and scalable architectures.
• Configure granular, country-based authorization and autonomy controls.
• Implement escalation logic with full context transfer across layers.
• Build and optimize embeddings, chunking, and indexing strategies.
• Enable cross-lingual retrieval and multi-language responses.
• Develop continuous data update pipelines and integrations.
• Integrate with WhatsApp, Discord, Telegram, LiveChat, email and in-app chat.
• Create unified per-user conversation histories and dashboards.
• Support human agents with N2 tools and seamless escalation.
• Develop a centralized dashboard for live conversations and agent metrics.
• Deploy on cloud servers (OVH, Digital Ocean, Linode) with Docker/Kubernetes HA.
• Monitor performance and optimize for low latency under load.

Kenntnisse

Multi-Agent AI Systems

Embeddings and Retrieval

LLM APIs (Claude, OpenAI, Grok, DeepSe

Sentiment Analysis

Model Context Protocol (MCP)

TypeScript/Node.js (NestJS)

TypeScript (React, Next.js)

RESTful APIs

WebSockets

Databases (PostgreSQL, MySQL)

NoSQL (MongoDB, Redis)

WhatsApp Business API

Discord/Telegram bots

Linux servers

Docker & Kubernetes

Git/version control

Real-time dashboards

Tools

CrewAI

AutoGen

LangGraph

WhatsApp Business API

Discord

Telegram

Docker

Kubernetes

PostgreSQL

MySQL

Jobbeschreibung

• Design and implement AI agent hierarchies using frameworks such as CrewAI, AutoGen, LangGraph, or a custom architecture
• Configure a granular authorization matrix by country, with autonomy control per capability
• Implement intelligent escalation logic between layers with full context transfer
• Design and implement an embeddings system with a chunking strategy and optimized indexing
• Implement cross-lingual retrieval (responses in multiple languages)
• Develop a continuous update pipeline as new data is generated
• Configure integrations with WhatsApp Business API, Discord (bot), Telegram (bot), LiveChat (widget), email, and in-app chat
• Implement unified cross-channel conversation history per user
• Ensure human-like behavior: configurable delays, typing indicators, natural language
• Integrate with internal APIs to execute automated actions (refunds, account management, diagnostics)
• Implement seamless escalation to human agents with zero context loss
• Develop AI assistance for human agents during N2 support
• Build a centralized dashboard: live conversations, agent metrics, queue management, KB editor, SLA monitoring
• Implement an N2 workstation for human agents with all necessary tools
• Create an audit log and analytics system for continuous improvement
• Deploy and manage on cloud servers (OVH, Digital Ocean, Linode)
• Containerize with Docker/Kubernetes for 24/7 high availability
• Monitor performance and optimize for fast response times under high load

Requirements

• Proven experience with multi-agent AI systems (CrewAI, AutoGen, LangGraph, or custom implementations)
• More than 2 years of experience with RAG/embeddings at scale (chunking, indexing, retrieval)
• More than 2 years of experience with multiple LLM APIs: Claude API, OpenAI API, Grok API, DeepSeek API, Kimi API, Gemini API
• Experience with sentiment analysis and natural language processing
• More than 2 years of experience with MCP servers (Model Context Protocol)
• More than 3 years of back-end experience with TypeScript/Node.js (NestJS)
• More than 3 years of front-end experience in TypeScript (React, Next.js) for dashboard development
• Experience with RESTful APIs and WebSockets for real-time communication
• Knowledge of relational databases (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis)
• Experience with WhatsApp Business API (or solutions like Twilio)
• Experience developing bots for Discord and/or Telegram
• Knowledge of human-in-the-loop design for AI systems
• Hands-on experience with Docker and Kubernetes
• Knowledge of Linux servers and deploying applications to production
• Best practices in version control (Git) and web application security
• Experience with real-time dashboards and monitoring

Core Competencies

Demonstrates expertise in designing and implementing multi-agent AI systems, including frameworks like CrewAI and AutoGen, with a strong focus on natural language processing, embeddings, and real-time communication. Proficient in developing and managing cloud-based solutions, ensuring high availability and performance optimization.

Highest-signal resume keywords

• Multi-Agent AI Systems
• Natural Language Processing
• Embeddings and Retrieval
• TypeScript/Node.js Development
• Docker and Kubernetes

ATS Optimization Keywords

Hard Skills

• Multi-Agent AI Systems
• Natural Language Processing
• Embeddings
• TypeScript
• Node.js
• React
• Next.js
• RESTful APIs
• WebSockets
• Sentiment Analysis

Industry Keywords

• Human-in-the-loop Design
• Model Context Protocol
• Real-time Dashboards
• Version Control
• Web Application Security

Tools & Technologies

• CrewAI
• AutoGen
• LangGraph
• WhatsApp Business API
• Discord
• Telegram
• Docker
• Kubernetes
• PostgreSQL
• MySQL