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Lead hands-on delivery of production AI solutions in customer environments. Design and implement NLP, LLM, speech, and agentic systems; build Python APIs, orchestration layers, integrations, and guardrails; and deploy scalable solutions on Azure. Collaborate with customers and technical teams to translate business processes into reliable applications while owning software quality, testing, observability, security, cost control, and operational excellence.

Owns the architecture, implementation, production readiness, and business outcomes of complex Data and AI systems, including agentic solutions. Leads senior engineering and data teams, establishes technical standards, manages risk and governance, contributes hands-on to delivery, and supports client engagements, pre-sales, and technical business development. The role also drives reusable architecture patterns, go-live stability, operational alignment, and long-term customer value.

Designs and operates scalable, secure Azure AI platforms using Terraform, Azure networking, RBAC, Key Vault, and policies. Builds GitHub Actions CI/CD pipelines, operationalizes models with MLflow, and deploys FastAPI inference services. Implements observability with OpenTelemetry and Azure Application Insights while improving reliability, performance, security, and automation. The role also supports AI engineers through self-service platform capabilities and production-ready model delivery.

Lead customer-facing implementation of production AI solutions using NLP, LLMs, and speech technologies. Design agentic workflows, orchestration, integrations, APIs, and decision logic while writing maintainable Python software. Deploy and operate scalable systems in Azure with strong reliability, observability, security, and cost controls. Collaborate directly with customers and internal engineering teams throughout workshops, architecture, implementation, and deployment.

A community interest opportunity for engineers, architects, product professionals, and builders interested in Data and AI. Members may receive invitations to meetups, technical workshops, deep-dives, and talks in Cologne, Munich, and Lisbon, hear about future Data and AI roles, and contribute as speakers or hosts.

Build and operate production-ready, AI-enabled software for enterprise customers. Responsibilities include translating ambiguous business needs into technical solutions, developing frontend and backend applications, creating integrations and cloud infrastructure, deploying and improving systems, and ensuring quality, security, scalability, and observability. The role involves customer workshops, technical communication, end-to-end ownership, and collaboration with engineering, AI, data, cloud, and QA teams.