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Frontend developer to HR platform with Angular experience
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2 X Senior AI Developer (Serverless & AWS)
Industries
Advertising
Information Technology (IT)
Areas
Information Technology (IT)
Marketing
Project info
- Period25.08.2025 - 07.01.2026
- Capacityfrom 95%
- Daily rate600 - 700€
- LocationMunich, Germany
- Languages
- German(Advanced),
- English(Advanced)
- German
- Remotefrom 95%
Description
We are looking for a highly skilled and experienced Senior AI Developer to join our AI & Automation team. In this role, you will design and implement cutting-edge AI solutions with a strong focus on autonomous agents, machine learning workflows, and cloud-native architectures to drive innovation in the marketing industry.
Our team develops intelligent, scalable systems that power automation and optimization across marketing channels — from content generation and personalization to campaign performance analysis and predictive insights. You will work at the intersection of AI, marketing technology, and software engineering, building serverless solutions on AWS that enable measurable business impact.
This is a hands-on technical role that requires deep expertise in AI system development as well as practical experience with AWS services and modern backend architectures. You’ll be part of a distributed, cross-functional team shaping how AI transforms marketing.
Responsibilities**
Design, develop, and deploy AI-driven systems and agent-based architectures on AWS
Build intelligent workflows using AWS serverless services (e.g. Lambda, Step Functions, DynamoDB, S3, EventBridge)
Integrate language models (Amazon Bedrock) into scalable applications
Develop and orchestrate autonomous agents for data processing, decision-making, or task automation
Design and optimize prompts to maximize the performance of LLM-based systems
Fine-tune foundational models and apply NLP techniques to align AI behavior with business needs
Collaborate with data scientists, backend engineers, and DevOps to bring AI models into production
Implement monitoring, logging, and error handling to ensure system reliability and performance
Design and integrate data ingestion and preprocessing workflows for structured and unstructured data
Ensure compliance with data protection policies and implement secure-by-design principles when handling confidential marketing data
Contribute to architecture and infrastructure decisions for AI services
Apply a “cloud-native” and “infrastructure-as-code first” mindset when designing and deploying solutions
Design systems with a clear understanding of stateful vs. stateless architectures and their impact on scalability, reliability, and cost
Requirements
5+ years of experience in software development, with at least 2 years focused on AI/ML systems
Strong experience with AWS, including Lambda, API Gateway, Step Functions, DynamoDB, S3, EventBridge, CloudWatch, IAM, Amazon Bedrock and SSM Parameter Store
Hands-on experience with prompt engineering and crafting effective interactions with LLMs
Experience in fine-tuning foundation models and applying natural language processing (NLP) techniques
Proven track record of building agent-based architectures or intelligent automation systems
Proficient in Python with solid understanding of software engineering best practices
Solid experience with Git/GitHub workflows and collaborative software development
Experience with event-driven and serverless architectures, and the ability to evaluate trade-offs with container-based approaches
Familiarity with MLOps concepts and tools (e.g. model deployment, monitoring, versioning)
Familiarity with infrastructure-as-code tools such as Terraform or AWS CloudFormation
Understanding of the full software development lifecycle (SDLC), from planning through deployment
Strong problem-solving skills and the ability to work independently in an agile, fast-paced environment
Excellent communication skills and the ability to collaborate across disciplines
Nice to Have**
Experience with vector databases (e.g. Pinecone, FAISS, Weaviate, ChromaDB, Milvus)
Knowledge of agent frameworks (e.g. LangChain, CrewAI, AutoGen, LangGraph)
Experience with real-time data processing (e.g. Kinesis, Kafka)
Familiarity with machine learning frameworks (e.g. TensorFlow, PyTorch)
Relevant AWS certification(s) like AWS Certified AI Practitioner
English
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