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Devoteam is a leading technology consulting firm specializing in digital transformation, cloud innovation, and AI. As a global AWS Premier Consulting Partner, we accelerate enterprise cloud journeys with over 11,000 experts.
Our AI & Machine Learning practice develops intelligent solutions and GenAI applications that transform business processes. As part of the AI Engineering team, you will implement cutting-edge machine learning solutions based on AWS AI/ML services such as SageMaker and Bedrock.
In your role as an AWS AI Engineer (m/f/d) and strategic advisor, you will design complex ML platforms and AI-based applications. You will work closely with customers, share your knowledge, and drive innovative, ethical AI solutions that deliver measurable business success. We are looking for creative problem solvers who want to challenge traditional processes through intelligent automation and strategically shape the AI transformation.
#AI DRIVEN TECH CONSULTING
Your benefits
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o Modern offices in prime locations in Frankfurt and Munich
o Hybrid working with the possibility to adapt your working hours and locations to your individual needs
o Our Devoteam Academy offers you a wide range of certified trainings and language courses
o International development opportunities for your career boost at Devoteam
o Gaming lounge for your creative break between meetings and calls
o Get-together parties and team events for regular exchange and fun with your colleagues
o Employee bonuses for recruiting new employees
o Modern IT equipment - Choose the right product for you from a wide range of options
o Corporate benefits with a wide selection of numerous offers for almost every area
o Job bike and company car offer with attractive tax benefits for you
o Company pension plans, direct insurance and capital-forming benefits are available to you as additional benefits
o Integration Day including mentoring programs for your perfect start at Devoteam
KEY JOB RESPONSIBILITIES
* End-to-End ML Platform Engineering: Design and implementation of scalable ML infrastructures with AWS SageMaker, MLflow, and Kubeflow for complete MLOps pipelines from experimentation to production
* GenAI Solution Development: Design and development of Large Language Model (LLM) applications with Amazon Bedrock, Custom Foundation Models, and RAG architectures for intelligent business applications
* Advanced ML Model Engineering: Development and deployment of custom machine learning models for computer vision, NLP, and predictive analytics with TensorFlow and PyTorch
* AI-Powered Application Architecture: Integration of AI services into existing business applications through MCPs, APIs, microservices, and event-driven architectures for seamless AI experiences
* MLOps and Model Governance: Building automated ML pipelines with CI/CD, model monitoring, A/B testing, and explainable AI for responsible AI implementation (ISO 42001)
* Real-time Inference Systems: Implementation of high-performance, latency-optimized ML inference systems with SageMaker Endpoints, Lambda, and container-based deployments
* Data Science Collaboration: Close collaboration with data scientists in the productionization of ML models and optimization of training/inference workflows
* AI Strategy Consulting: Advising clients on AI adoption strategies, use case identification, and technology selection for successful AI transformations
A DAY IN THE LIFE
Your day often begins with a review of ML model performance metrics and monitoring dashboards to ensure that all production AI services are functioning optimally. You'll then conduct a technical stand-up with your AI engineering team to discuss the progress of current ML implementations and address any potential challenges with model deployment.
The mornings are often characterized by innovation sessions with customers, in which you evaluate AI use cases and conduct technical feasibility studies—be it the implementation/design of IDPs, RAG systems, or the development of a custom GenAI application for automation. You will work closely with product owners and business stakeholders to ensure that the AI solution generates real added value.
In the afternoons, you'll focus on hands-on development and experimentation: You'll optimize hyperparameters for better model performance, develop new feature engineering pipelines, and implement techniques like prompt engineering and fine-tuning for LLMs. An important part of your work will also be technical mentoring of junior AI engineers—you'll share your expertise in code reviews and lead workshops on modern ML engineering practices.
You will often conclude your day with research and innovation activities, where you will evaluate new AWS AI services, develop proof-of-concepts for emerging AI technologies, or work on thought leadership content such as technical blogs or conference presentations.
BASIC QUALIFICATIONS
* 3+ years of experience in machine learning engineering, AI development, and deployment of ML models in productive environments
* Solid knowledge of AWS AI/ML services (SageMaker, Bedrock, Comprehend, Rekognition, Textract) and their integration into business applications
* Programming expertise in Python with extensive experience in ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face)
* MLOps and DevOps knowledge for automated ML pipelines, model versioning and container-based deployments
* Solid mathematical and statistical foundations for understanding ML algorithms and model evaluation
* Excellent problem-solving skills and the ability to translate complex business problems into AI solutions
* Fluent German and English skills for international AI projects and global collaboration
PREFERRED QUALIFICATIONS
* AWS AI/ML certifications (Machine Learning Specialty, Data Analytics) or comparable industry certifications
* GenAI and LLM expertise with practical experience in prompt engineering, fine-tuning and RAG implementation
* Deep Learning specialization in Computer Vision, NLP or Reinforcement Learning with proven project success
* Cloud-native AI Architecture Experience with Serverless ML, Edge AI and Multi-Cloud AI Deployments
* Responsible AI Knowledge of bias detection, explainable AI and AI ethics for regulated industries
* Research background with scientific publications, patents or contributions to open-source ML projects
* Industry-specific AI experience in areas such as Healthcare AI, FinTech ML or Industrial IoT Analytics
* Thought Leadership durch AI Conference Presentations, Technical Blogging oder Community Contributions
Contact our recruiting team
Thanks to our open corporate culture, we place great value on giving people the opportunity to apply, even if they don't meet all the specific skills listed in the job description. We believe that with our support and a motivated team, every individual can reach their full potential.
We look forward to receiving your application!