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As an AI Solution Architect, you'll lead AI strategies, design architectures, evaluate frameworks, ensure compliance, and collaborate with teams for production deployment in enterprises.

The Pre-Sales Engineer will provide technical expertise in AI and data platforms, support clients during pre-sales engagements, and help design AI solutions aligning with business goals.

Lead end-to-end delivery of AI, ML, Big Data, and software projects for international enterprise clients. Act as primary client contact, define scope, manage risks, budgets, and resources, mentor cross-functional teams, drive business-aligned technical roadmaps, support pre-sales, and contribute to account growth and recruitment.

As an AI Engineer (GCP), you'll develop and implement AI solutions, lead teams, design architectures, and optimize AI workloads, focusing on LLM usage data.

As a Data Engineer, you'll design and maintain scalable data pipelines and analytics solutions in GCP, focusing on LLM usage analytics, data transformation, and collaboration with teams to ensure high-quality data processing.

Own the full enterprise sales cycle to acquire new clients for AI, generative AI, data engineering, and analytics services. Prospect and qualify opportunities, engage C-level stakeholders, develop proposals with Pre-Sales and Delivery, negotiate contracts, manage pipeline and forecasting, represent the company at events, and support GTM and handover to delivery and customer success.

Own the full sales cycle for enterprise AI, Generative AI, data engineering and analytics opportunities in the DACH region: prospecting, engaging C-level stakeholders, developing proposals, negotiating contracts, forecasting pipeline, and representing the company at industry events while collaborating with Pre-Sales, Delivery, Marketing, and Strategic Alliances.

Drive and scale Addepto’s technology partner ecosystem by building executive relationships with major AI and cloud vendors, creating co-sell pipelines, executing joint go-to-market campaigns, enabling internal teams, tracking partnership KPIs, and reporting progress to leadership to generate partner-sourced revenue and market visibility.

Design and implement scalable batch and streaming data pipelines on Databricks and cloud platforms; build data transformations, CI/CD and MLOps practices; collaborate with data scientists; create data governance, monitoring, and Power BI visualizations; translate business requirements into performant technical solutions.

Lead design and implementation of scalable, secure architectures bridging legacy systems and cloud-native platforms. Provide technical leadership, define integration patterns (WebLogic, IBM MQ, Kafka), apply DDD, leverage Azure and Kubernetes, document architectures, and mentor teams to ensure performance, reliability, and alignment with business goals.