Agentic AI Software Engineer

Machine Learning Reply·Munich, Bayern, Germanymid

In short

→Ingeniero de software con enfoque en IA autónoma y generativa, desarrollando sistemas productivos para clientes.
→Días típicos: diseño de pipelines de IA, integración de LLMs, despliegue en cloud, colaboración con equipos y clientes.
→Destacado: Trabajo en proyectos innovadores con tecnología punta en múltiples sectores (banca, automoción, retail, etc.).

Fluent in English and at least C1-level German. This requirement is mandatory.

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What they ask for

✓Formación universitaria técnica (Ciencias de la Computación, Ingeniería, etc.).
✓Experiencia práctica en despliegue de modelos de IA/ML en producción.
✓Habilidad en dos lenguajes: Python, Java, Rust o JavaScript.
✓Conocimientos en LLMs, ingeniería de prompts, fine-tuning e integración de IA generativa.
✓Experiencia con bases de datos (SQL y NoSQL) y modelado de datos.
✓Nivel C1 de alemán y inglés fluido (requerido).

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

AWSGCPAzureFastAPIFlaskSpring BootLangChainLangGraphvector databasesRAG pipelines

Who should you write to at Machine Learning Reply?

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We are looking for a skilled and motivated Consultant to join our team. The ideal candidate combines strong software engineering expertise with hands-on experience in modern AI systems, including agentic AI and generative AI applications. You will support our clients in designing and building intelligent, production-ready systems that leverage LLMs, autonomous agents, and scalable cloud architectures. 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. ). · 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. , 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. Qualifications: · 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.

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