Jobs at Fetcherr

Serve as the ferry revenue management and pricing authority for an AI-driven optimization product. Define operational data requirements, business rules, regulatory constraints, and modeling logic; validate pricing outputs; guide product and engineering teams; support customer implementations, workshops, commercial opportunities, and industry strategy. Expertise should cover passenger, vehicle, accommodation, and ro-ro freight inventory, demand forecasting, dynamic pricing, ancillary revenue, and ferry-specific KPIs.

Lead the production engineering organization responsible for the market model’s data pipelines, ML training and serving, infrastructure, monitoring, reliability, and costs. Set roadmaps and priorities across MLOps, ML engineering, and data engineering; manage functional leads; oversee delivery, KPIs, hiring, technical standards, and cross-functional collaboration. Partner with applied research to productionize models and communicate progress, risks, and technical decisions to executives, product, commercial teams, and engineers.

Leads production engineering for an AI market model, overseeing MLOps, machine learning engineering, data engineering, infrastructure, data pipelines, model training and serving, monitoring, reliability, costs, KPIs, and delivery. Manages functional leads, sets technical roadmaps and standards, partners with applied research and commercial teams, hires senior engineers, and ensures machine learning systems operate reliably in customer-facing production environments.

Manage strategic client relationships across multiple industries, serving as the primary contact and ensuring satisfaction, commercial performance, and solution alignment. Translate client goals into actionable plans, lead cross-functional initiatives, support renewals and cross-sell opportunities, monitor performance metrics, resolve issues, and represent customer needs internally. Frequent travel to Genoa, Italy is required for client meetings and on-site engagements.

Provides frontline technical and data support for Fetcherr’s platform while monitoring data pipelines and production workflows. Responsibilities include troubleshooting user issues, identifying and resolving pipeline problems, maintaining production schedules and activity records, communicating delays to stakeholders and customers, and coordinating with data engineering, R&D, product, and other teams. The role follows rotating day, evening, night, and weekend shifts.

Own complex enterprise support escalations from investigation through resolution within SLA. Diagnose data pipeline failures, maintain runbooks and knowledge systems, improve R&D handoff quality, develop product expertise, and represent support in customer meetings. Collaborate with R&D to reduce recurring issues and improve products. The role requires Python, SQL, data pipeline orchestration, customer communication, and experience building agentic AI workflows to streamline support operations.

Manage strategic enterprise client relationships across multiple verticals, serving as the primary contact and ensuring satisfaction, commercial performance, product adoption, renewals, and successful delivery. Translate client goals into actionable plans, coordinate cross-functional teams, monitor performance metrics, identify expansion opportunities, and represent customer needs internally. Requires frequent travel to Genoa, Italy, approximately twice monthly.

Architect and operate a secure, self-service platform on GCP and Kubernetes. Build controllers, operators, infrastructure-as-code workflows, and GitOps delivery pipelines. Establish observability, SLOs, alerting, reliability, and recoverability standards while leading blameless postmortems. Develop production-quality Go or Python software, enforce security and supply-chain controls, and enable independent service lifecycles across global markets.

Own the end-to-end architecture of a scalable, cloud-native agentic platform on Azure. Establish Kubernetes, infrastructure-as-code, GitOps, CI/CD, observability, and production standards; write core code; guide engineers without direct management; collaborate with the Chief AI Officer; build integrations across enterprise platforms; and enable AI-assisted software development.

Own the end-to-end architecture of a greenfield, cloud-native Azure platform. Design Kubernetes-native infrastructure, IaC, GitOps, CI/CD, observability, and integrations with major enterprise platforms. Lead core coding, establish engineering standards, collaborate with the Chief AI Officer to productize decisioning methodologies, and build an AI-enabled SDLC. Guide engineers without direct management and take the system from proof of concept to production.

Own and lead Fetcherr’s product function, including strategy, roadmap, lifecycle execution, and product team growth. Manage and mentor Product Managers, collaborate with Engineering, Data, and Design, and engage enterprise airline customers on requirements and roadmap direction. Partner with Sales and Customer Success to support onboarding, renewals, and expansion. Translate complex AI capabilities into user-friendly products and measurable commercial value while driving execution, prioritization, and accountability.

Build and maintain Tableau reports and dashboards, administer Tableau Server, and translate complex datasets into clear insights for non-technical stakeholders. Work with SQL and ETL pipelines to integrate and optimize large-scale data, troubleshoot performance, and support analytics team deliverables. Communicate findings, collaborate with peers, and continuously learn.

Manage strategic client relationships across multiple industries, serving as the primary account contact and aligning Fetcherr’s AI products with customer objectives. Drive client initiatives, stakeholder coordination, product adoption, cross-sell opportunities, renewals, commercial discussions, and issue resolution. Analyze performance metrics, provide strategic recommendations, and represent client needs internally. Frequent travel to Genoa, Italy, approximately twice monthly, is required.

Build and administer Tableau dashboards and reports, transform large datasets into actionable insights, optimize queries and ETL processes, collaborate with stakeholders, and support Tableau Server administration and performance monitoring.

Build and maintain scalable ML models and data pipelines for training and inference. Ensure data accuracy and efficiency across structured and unstructured sources, using orchestration, containerization, and distributed systems to support data science workflows.

Design and operationalize causal-uplift measurement frameworks, lead data discovery, research novel uplift/A-B testing approaches, translate multidimensional pricing data into business insights, and collaborate with revenue managers, analysts, and engineers to encode airline business logic into modeling pipelines.

Build and maintain models and data pipelines for training and inference. Ensure data accuracy, consistency, and scalability across structured and unstructured sources. Implement pipeline orchestration, containerized deployments, and distributed computing to support data science workflows and production ML systems.

Design and operationalize causal uplift measurement frameworks, lead data discovery, conduct research and experiments for uplift/A-B testing, translate complex data into actionable pricing insights, assess ML system impact in business contexts, and collaborate with revenue managers, analysts, and engineers to encode airline business logic into modeling and pipelines.

Build and maintain scalable ML models and data pipelines, ensuring data quality for training and inference. Implement MLOps practices using orchestration, containerization, and distributed systems to support data science workflows.

Build and maintain scalable ML models and data pipelines for training and inference. Ensure data accuracy and efficiency across structured and unstructured sources, work with orchestration, containerization, and distributed systems to support production ML workflows and collaboration with data science teams.