Define and own the AI Engineering strategy and contribute to the development of machine-learning-powered products.
Lead and grow a cross-functional team, ensuring effective collaboration with product managers, data teams, and technology stakeholders.
Establish standards and processes for AI-native product development, including CI/CD with evaluations, test data sets, and search subsystems.
Select and implement best-in-class tools (open-source and commercial), including AI evaluation stacks, MCP Servers, A2A communications, and pipelines.
Design AI-native workflows involving streaming, long-running tasks, and procedural UX, balancing state-of-the-art technology with pragmatism.

Key requirements

Define and own the AI Engineering strategy and contribute to the development of machine-learning-powered products.
Lead and grow a cross-functional team, ensuring effective collaboration with product managers, data teams, and technology stakeholders.
Establish standards and processes for AI-native product development, including CI/CD with evaluations, test data sets, and search subsystems.
Select and implement best-in-class tools (open-source and commercial), including AI evaluation stacks, MCP Servers, A2A communications, and pipelines.
Design AI-native workflows involving streaming, long-running tasks, and procedural UX, balancing state-of-the-art technology with pragmatism.

Jobs at InPost Group

1 active role from this employer in the JobMatcher catalog.

All company jobs

Jobs at InPost Group

1 active role from this employer in the JobMatcher catalog.

All company jobs

About the role

InPost Group is a European leader in out-of-home deliveries. We are seeking an AI Engineering Manager to join the Data & AI organization in Krakow and lead AI-native product development across the Group. You will lead a multidisciplinary engineering team of approximately 10–15 engineers, support their growth and collaboration, and own the AI Engineering strategy.

Responsibilities

Technologies and areas you may work with: Python, LangSmith, AI evaluation tools, OpenAI, Gemini, Databricks, multi-agent systems, MCP Se

Define and own the AI Engineering strategy and contribute to the development of machine-learning-powered products.
Lead and grow a cross-functional team, ensuring effective collaboration with product managers, data teams, and technology stakeholders.
Establish standards and processes for AI-native product development, including CI/CD with evaluations, test data sets, and search subsystems.
Select and implement best-in-class tools (open-source and commercial), including AI evaluation stacks, MCP Servers, A2A communications, and pipelines.
Design AI-native workflows involving streaming, long-running tasks, and procedural UX, balancing state-of-the-art technology with pragmatism.
Drive improvements in system architecture, application design, and engineering processes to enhance product functionality and customer experience.
Contribute to hiring, onboarding, and the professional development of team members, fostering a diverse and inclusive workplace.
Collaborate with strategic vendors and technology partners on partnerships and service agreements.

About the role

InPost Group is a European leader in out-of-home deliveries. We are seeking an AI Engineering Manager to join the Data & AI organization in Krakow and lead AI-native product development across the Group. You will lead a multidisciplinary engineering team of approximately 10–15 engineers, support their growth and collaboration, and own the AI Engineering strategy.

Responsibilities

Technologies and areas you may work with: Python, LangSmith, AI evaluation tools, OpenAI, Gemini, Databricks, multi-agent systems, MCP Se

Define and own the AI Engineering strategy and contribute to the development of machine-learning-powered products.
Lead and grow a cross-functional team, ensuring effective collaboration with product managers, data teams, and technology stakeholders.
Establish standards and processes for AI-native product development, including CI/CD with evaluations, test data sets, and search subsystems.
Select and implement best-in-class tools (open-source and commercial), including AI evaluation stacks, MCP Servers, A2A communications, and pipelines.
Design AI-native workflows involving streaming, long-running tasks, and procedural UX, balancing state-of-the-art technology with pragmatism.
Drive improvements in system architecture, application design, and engineering processes to enhance product functionality and customer experience.
Contribute to hiring, onboarding, and the professional development of team members, fostering a diverse and inclusive workplace.
Collaborate with strategic vendors and technology partners on partnerships and service agreements.

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