- מיקום
- כל הארץ
- היקף משרה
- משרה מלאה
- תפקיד
- דאטה סיינטיסט
תיאור המשרה
Description
Join the company and help scale AI capabilities across the organization. As the AI IT Centre of Excellence (COE) Deploy Lead, you will own the methodologies, standards, and deployment practices that make AI implementation repeatable and reliable across Strauss.
You will act as the professional focal point for AI delivery — working alongside AI experts, data teams, software developers, architects, and business stakeholders to ensure consistent, high-quality delivery of AI initiatives while building organizational knowledge and capability.
Employment model: Israel-based, offshore/outsourcing engagement (not a buy-out).
Key Responsibilities
- Lead the deployment methodology, standards, and best practices of the AI IT Centre of Excellence (COE).
- Guide and support development teams in the design, implementation, and adoption of AI solutions.
- Serve as the professional focal point for AI delivery frameworks, tools, architectures, and implementation approaches across the organization.
- Facilitate collaboration between AI experts, data teams, software development teams, architects, and technology stakeholders.
- Provide training, coaching, and ongoing enablement for teams delivering AI initiatives.
- Build and maintain AI playbooks, implementation guidelines, reference architectures, templates, and knowledge assets.
- Drive consistency, quality, governance, and scalability across AI implementations.
- Support project execution, manage dependencies, identify risks, and help teams overcome implementation challenges.
- Lead AI knowledge-sharing activities, communities of practice, and professional development programs.
Requirements
- 4+ years of experience in software development, data, analytics, AI, or related technology domains.
- Hands-on experience with Python, APIs, data platforms, cloud technologies, and AI tooling.
- Strong understanding of AI, GenAI, LLMs, automation, and modern technology architectures — including how LLM solutions are actually built and evaluated (RAG, prompting, agents, guardrails).
- Practical grasp of AI delivery methodology: standards, governance, and the operational practices that keep AI solutions reliable in production.
- Ability to translate business needs into technical requirements and actionable implementation plans.
- Experience working with cross-functional development and technology teams.
- Strong facilitation, training, and stakeholder management skills.
- Ability to produce clear solution/reference architecture and technical documentation.
- Excellent communication and presentation abilities.
- Self-driven, proactive, and engaged with AI and emerging technologies.
