Senior Agentic AI Engineer

Jobtailor; Deutschland; Remote; EUR 120.000 - 170.000; Vollzeit

Zusammenfassung

Jobtailor seeks an AI architect to design and build scalable Generative AI applications end to end, focusing on LLM-powered workflows and agentic systems. You will mentor engineers and collaborate with product and customers to shape the long-term AI platform strategy.

The role requires strong ML background, Python expertise, and hands-on LangChain/LangGraph experience. Join a fast-paced environment where ownership is valued and cross-functional teamwork drives enterprise AI adoption, with a

Qualifikationen

• 6+ years in traditional ML with 2+ years in Generative AI
• Strong experience with LLMs and prompt engineering
• Real-world LangChain/LangGraph experience
• Strong Python skills for API wrappers and tooling
• Foundation in Transformers, TensorFlow, PyTorch
• Experience with NLP, embeddings, and vector databases
• Hands-on with OpenAI, Llama/Llama2, Azure OpenAI
• Experience designing distributed, cloud-native architectures (microservices)
• Proficiency with AWS/Azure/GCP and Docker/Kubernetes
• MLOps/LLMOps experience
• Excellent communication skills
• Bachelor's/Master's in CS/Data Science/Engineering
• Comfort with startup pace and ownership mentality
• Preferred: LoRA/RLHF/PEFT
• Preferred: GPU/TPU optimization
• Preferred: AI governance/compliance familiarity
• Preferred: Consulting or enterprise AI product shipping
• Preferred: Industry experience in financial services/healthcare/insurance

Aufgaben

• Architect and build scalable Generative AI applications end to end
• Design LLM-powered workflows and prompt strategies for multi-agent systems
• Build intelligent AI agents using LangChain and LangGraph for NL-to-SQL, autonomous tasks, and RAG pipelines
• Select, customize, fine-tune, and optimize state-of-the-art LLMs
• Design and own full ML/GenAI pipelines incl. training, deployment, monitoring
• Build APIs, microservices and integration frameworks to bring AI to products
• Champion responsible AI by mitigating hallucinations, bias and reliability risks
• Partner with customers, product and engineering to translate business needs into robust AI architecture
• Mentor engineers and help shape long-term AI platform strategy

Kenntnisse

Generative AI Experience

LLM Proficiency

Python Programming Skills

MLOps/LLMOps Knowledge

LangChain/LangGraph Expertise

Communication Skills

Ownership Mentality

Ausbildung

Bachelor's in CS

Master's in Data Science

Tools

Docker

Kubernetes

OpenAI

API Development

Microservices

Vector Databases

AWS

Azure

GCP

LangChain/LangGraph

Jobbeschreibung

Architect and build scalable Generative AI and agentic AI applications end to end
Design LLM-powered workflows and prompt strategies for reflexive, self-learning, multi-agent systems
Build intelligent AI agents using LangChain and LangGraph for NL-to-SQL, autonomous task agents, and RAG pipelines
Select, customize, fine-tune, and optimize state-of-the-art LLMs
Design and own full ML/GenAI pipelines, including training, deployment, monitoring, and lifecycle management
Build APIs, microservices, and integration frameworks to bring AI into enterprise products
Champion responsible AI practices by mitigating hallucinations, bias, and reliability risks
Partner directly with customers, product, and engineering to turn business needs into robust AI architecture
Mentor engineers and help shape the long-term AI platform strategy

Requirements

• 6+ years in traditional ML, including 2+ years hands-on with Generative AI
• Strong experience with LLMs (GPT and similar), prompt engineering, and agentic systems
• Real-world experience with LangChain/LangGraph or similar agentic frameworks
• Strong Python skills — API wrappers, third-party integrations, internal tooling
• Solid foundation in Transformers, CNNs, RNNs — hands-on with TensorFlow, PyTorch, Scikit-learn
• Experience with NLP, embedding models, and vector databases
• Hands-on work with OpenAI, Llama/Llama2, Azure OpenAI, and other open-source models
• Experience designing distributed, cloud-native architectures (microservices, REST APIs)
• Proficiency with AWS, Azure, or GCP, plus Docker/Kubernetes
• MLOps/LLMOps experience — training, deployment, monitoring, lifecycle management
• Excellent communication skills — translate technical depth for non-technical stakeholders
• Bachelor's or Master's in CS, Data Science, Engineering, Math, Statistics, or related field
• Comfort with startup pace and strong ownership mentality
• Preferred: LLM fine-tuning experience (LoRA, RLHF, PEFT)
• Preferred: Performance optimization (GPU/TPU acceleration, quantization, pruning, distillation)
• Preferred: AI observability/monitoring tool experience
• Preferred: Familiarity with AI governance and compliance (GDPR, SOC 2)
• Preferred: Prior consulting or solution-architecture experience shipping enterprise AI products
• Preferred: Background in financial services, healthcare, or insurance

Core Competencies

Demonstrates expertise in architecting and building scalable Generative AI applications, with a strong focus on LLMs, prompt engineering, and agentic systems. Proficient in designing and managing full ML/GenAI pipelines, while championing responsible AI practices and mentoring engineering teams.

Highest-signal resume keywords

• Generative AI Experience
• LLM Proficiency
• LangChain/LangGraph Expertise
• Python Programming Skills
• MLOps/LLMOps Knowledge

Hard Skills

• Generative AI
• LLMs
• Prompt Engineering
• LangChain
• LangGraph
• Python
• Transformers
• TensorFlow
• PyTorch
• NLP

Soft Skills

• Excellent Communication Skills
• Ownership Mentality

Certifications & Qualifications

• Bachelor's in CS
• Master's in Data Science

Industry Keywords

• AI Governance
• Compliance
• Financial Services
• Healthcare
• Insurance

Tools & Technologies

• AWS
• Azure
• GCP
• Docker
• Kubernetes
• OpenAI
• Llama
• API Development
• Microservices
• Vector Databases