Job details:

• Full-time
• 100% Remote
• Start date: ASAP
• End date: 24/12/2026

As part of the Business AI program, the client is building two agents that streamline core processes and boost productivity, freeing sales and post sales to focus on meaningful customer work and accelerate time to value.

We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI and Generative AI solutions that deliver measurable business value. This role requires strong software engineering fundamentals combined with hands-on experience deploying LLM-powered systems into production environments.

You will drive AI initiatives from proof-of-concept through secure, scalable enterprise deployment.

Responsibilities:

• Design, Develop, and Deploy: Create robust AI and generative AI services and solutions, guiding them from proof of concept to full enterprise deployment.
  • Build Scalable Systems: Architect scalable and secure AI systems with effective data pipelines and model deployment workflows.
  • Implement Best Practices: Champion CI/CD and MLOps practices to enhance automation of model training, testing, and deployment processes.
  • Collaborate for Success: Work closely with AI Product Owners, data scientists, and other stakeholders to translate requirements into reliable, production-ready systems.
  • Innovate with Multi-Agent Systems: Develop and integrate multi-agent AI and LLM-based products to advance our business capabilities.
  • Ensure Excellence: Maintain high standards of reliability, observability, and compliance in deployed AI solutions.

Requirements:

• 5+ years of professional software engineering experience
  • Strong expertise in Python (required) and at least one additional language (Node.js or Java)
  • Backend Proficiency: Experience with frameworks like FastAPI, Flask, Django and developing microservices architectures.
  • Containerization Knowledge: Familiarity with Docker, Kubernetes, and orchestration tools such as GitHub Actions and MLFlow.
  • Cloud Experience: Implement CI/CD and MLOps pipelines in cloud environments like Azure ML, Databricks, or AWS.
  • Data Expertise: Hands-on experience with ETL processes, API integration, and model deployment workflows.
  • System Design: Knowledge of distributed systems and platforms for big data processing.
  • Agile Practices: Understanding of Agile frameworks (Scrum, Kanban) and collaborative engineering practices.
  • Language Proficiency: Fluent English with a proactive, problem-solving mindset.

Nice to have:

• Advanced AI Knowledge: Experience with multi-agent or generative AI frameworks like LangChain or CrewAI.
  • SAP Familiarity: Experience with SAP AI Core and SAP BTP.
  • Project Management Tools: Experience with agile frameworks and tools like Jira (Scrum, SAFe).

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