Jobs at Fetcherr

Lead a team of AI engineers to develop early-stage products, drive research, manage innovation pipelines, and build a high-performing team.

Architect and build a self-service, Kubernetes-native platform: implement controllers/operators, infrastructure-as-code, GitOps CI workflows, production observability and SLOs, and secure, automated developer pathways to enable rapid, reliable delivery.

Architect and build a self-service, Kubernetes-native platform: implement controllers/operators, everything-as-code (Terraform/Helm/GitOps), enable secure automated developer workflows, and own production reliability, observability, SLOs, and incident postmortems.

Lead strategy and execution for Fetcherr's AI-driven enterprise platform. Own product domains end-to-end, drive discovery, define requirements, partner with engineering and data science, conduct user research, measure product performance, and support customer engagements and deployments to deliver scalable, data-driven solutions.

Manage strategic enterprise accounts as primary client contact, ensuring satisfaction, commercial performance, renewals, product adoption, and alignment with client objectives. Coordinate cross-functional teams, analyze client metrics, identify upsell/cross-sell opportunities, influence product development with client feedback, and travel for meetings and QBRs.

Design and implement the decision-making logic of a Price Optimizer: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, write tested maintainable code, validate model behavior with data, and collaborate with Solution Architects and Data Engineers to integrate models into Dagster pipelines.

Design and implement the Price Optimizer decision logic: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, write tested maintainable code, validate model behavior, and collaborate with Solution Architects and Data Engineers to integrate into Dagster pipelines.

Design and implement the Price Optimizer's decision logic: translate pricing rules into mathematical models and production-ready Python code, develop and tune simulation and optimization algorithms, write tested maintainable code, analyze model behavior and edge cases, and collaborate with solution architects and data and engineering teams to integrate models into Dagster pipelines.

Design and implement decision-making logic for a price optimizer: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, validate model behavior using data, and collaborate with architects and data engineers for pipeline integration.

Design and implement pricing decision logic and optimization models in production-quality Python. Translate business rules into mathematical constraints, validate model behavior with data, collaborate with Solution Architects and Data Engineers to integrate models into Dagster pipelines.

The AI Data Engineer will design and build AI data pipelines, ensuring reliability and quality for predictive intelligence in the Large Market Model.

As an AI Data Engineer, you will design and implement data pipelines for the Large Market Model (LMM), focusing on feature engineering, system reliability, and driving innovation through advanced AI technologies.

The AI Data Engineer will develop and maintain AI data pipelines, ensure system reliability, and innovate within AI technologies.

The AI Data Engineer will develop and maintain data pipelines for the Large Market Model, focusing on feature engineering, system reliability, and innovation in AI solutions.

The AI Data Engineer will architect and engineer data pipelines for the Large Market Model (LMM), ensuring system reliability and exploring innovative features in AI-driven solutions.

The Director of Product will define strategy for complex product domains, drive execution, and ensure real customer value through AI-driven products.

The Escalation Leader manages R&D escalations, coordinates incident responses, drives process improvements, and builds relationships between support and engineering teams.

Manage strategic enterprise client relationships to ensure satisfaction, commercial performance, product alignment, renewals, and adoption. Coordinate cross-functional teams, analyze client performance metrics, identify expansion opportunities, and represent client needs to influence product and service improvements. Travel to client meetings and industry events as needed.

The Program Manager will lead program delivery for key customers, manage Agile processes, and oversee product delivery while collaborating with cross-functional teams.

As Director of Engineering, lead technical and organizational efforts, manage R&D teams, drive innovation in AI-driven products, and align technical strategies with customer needs.