Delivery Lead

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SeniorFull-time·B2B
#355670·Dodano dziś·0
Źródło: emagine
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Tech Stack / Keywords

AIArchitectureSecurityGoAgileData ScienceLLMSoftware Architecture

Firma i stanowisko

The role is within the Transportation / Logistics industry, focusing on delivering AI solutions that align business needs with technical capabilities to create organizational value.


Wymagania

  • Bachelor’s degree in IT, Computer Science, Data Science, Business Informatics, or a related field.
  • 10+ years of proven experience in agile product or software delivery.
  • Strong understanding of backlog management and delivery flow.
  • Working knowledge of AI / ML / LLM / RAG solutions.
  • Understanding of software architecture, APIs, and integrations.
  • Familiarity with AI governance, security, and data privacy principles.
  • Ability to translate business needs into technical implementation plans.
  • Team player with excellent communication skills.
  • Flexible thinker able to operate in a dynamic environment.
  • Experience in cross-functional enterprise teams.
  • Fluent in Business English (written and spoken).
  • Working knowledge of Jira / Confluence and MS Office.

Nice to have:

  • Experience with enterprise systems, integrations, or digital platforms.
  • Experience in AI, automation, analytics, or data-driven solutions.
  • Experience managing dependencies, risks, and delivery timelines.
  • Experience in logistics or large-scale corporate environments.

Obowiązki

  • Identify, assess, and shape demand for AI solutions across internal and external customers.
  • Translate business needs into technical scope, requirements, and backlog items.
  • Lead technical delivery from discovery through production release.
  • Own backlog, refinement, sprint readiness, and delivery flow.
  • Coordinate forward deploy engineers, data scientists, developers, QA, and platform teams.
  • Make technical delivery decisions and manage dependencies.
  • Ensure architecture, security, compliance, and operational standards are met.
  • Implement AI controls such as monitoring and human oversight.
  • Track delivery progress, support go-live, and follow up on value realization.
  • Promote standardization and scalable implementation patterns across initiatives.
  • Lead squads assigned for development and maintenance tasks using agile methodologies.
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