Agentic AI Software Engineer
Indexed description
Responsibilities:
- Design, build, and deploy scalable, production-grade systems on cloud platforms such as AWS, GCP, or Azure.
- Develop and operate agentic AI systems, including multi-step workflows, tool integration, and autonomous decision-making components.
- Lead end-to-end implementation of AI-driven features, from prototyping (PoC) to production deployment.
- Build high-performance APIs and backend services for AI applications using frameworks such as FastAPI, Flask, or Spring Boot.
- Integrate generative AI solutions (LLMs, vector databases, RAG pipelines, orchestration frameworks like LangChain/LangGraph) into enterprise environments.
- Design and implement robust orchestration and retrieval pipelines for scalable AI applications.
- Set up and maintain MLOps / LLMOps pipelines and CI/CD workflows for continuous integration, evaluation, and deployment.
- Ensure software quality through testing, monitoring, observability, and performance optimization.
- Collaborate closely with clients and cross-functional teams to identify requirements and deliver impactful AI solutions.
- Work on innovative AI and Software Engineering projects across industries (Banking, Insurance, Automotive, Retail, etc.).
- Expand your skills in areas such as MLOps, cloud architecture, data engineering, and generative AI.
- Collaborate with top technology partners in the cloud, AI, and automation ecosystem.
- Access to training, certifications, and interdisciplinary projects.
- Join a vibrant community with hackathons, conferences, and knowledge-sharing events.
- Award-winning office space in downtown Munich with great transport connections.
- Flexible working model between client site, Reply office, and remote work.
Job Requirements
Minimum Qualifications:
- Completed university studies with a strong quantitative or technical background (e.g., Computer Science, Data Science, Engineering, or similar).
- Ideally, you have already gained some initial consulting and project management experience Teamwork & Collaboration – ability to work effectively with others toward common objectives.
- Adaptability – flexibility in taking on different roles within a team and understand the need of the costumer
- Solid programming experience in at least two programming languages such as Python, Java, Rust, or JavaScript.
- Practical experience deploying ML/AI models into production environments (on-premises or cloud).
- Experience with different database technologies, including SQL and NoSQL, with knowledge of database design, data modeling, and data management.
- Experience with large language models (LLMs), prompt engineering, fine-tuning, and integrating generative AI into actual solutions.
- Strong communication skills for explaining technical concepts to both technical and business stakeholders.
- Fluent in English and at least C1-level German. This requirement is mandatory.
- Hands-on experience with cloud AI services.
- Understanding of MLOps concepts (model registry, monitoring, CI/CD).
- Knowledge of modern AI/ML frameworks and tools such as PyTorch, TensorFlow, Hugging Face, LangChain, or OpenAI APIs.
- Awareness of software engineering principles (SOLID, testing, version control).
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Cloud certifications are a plus.
- Teamwork & Collaboration – ability to work effectively with others toward common objectives.
- Adaptability – flexibility in taking on different roles within a team and understand the need of the costumer
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