AI Engineer

תיאור תפקיד

We’re hiring an AI Lead with strong technical depth and sharp business instincts. You’ll own the full lifecycle of AI solutions—from design and data to deployment and scale—while earning stakeholder trust and driving measurable impact
What you’ll do:
•    Own end to end delivery of AI solutions
•    Translate business needs into AI solutions
•    Build & automate prototype quickly, then develop solutions using modern low/no-code platforms
•    Integrate responsibly: Help define and follow security, privacy, and compliance standards; contribute to platform evaluations and the AI platform approval process.
•    Drive adoption & change: create simple runbooks, demos, and training; enable business teams to use and maintain solutions.
•    Measure impact: define KPIs at the outset (time saved, quality uplift, throughput, ROI) and report outcomes to stakeholders.
What you’ll bring:
•    Technical foundation: 2+ years in software/data/ML roles; knowledge in Python (or similar), cloud services, vector databases/RAG, and MLOps practices.
•    Proven end to end execution: shipped multiple Agentic/Automation/ML projects into production with real users and measurable results.
•    Automation mindset: experience with workflow automation, low/no code integrations, or agent frameworks tied to business processes.
•    Data fluency: comfort with data modeling, ETL/ELT, evaluation, and experiment design; pragmatic about data constraints.
•    Business partnering exceptional listening and framing skills; you simplify complexity, set expectations, and earn trust with non technical partners.
•    Product thinking: prioritize, iterate fast, and land solutions that stick (usable, reliable, secured, supported).
•    Communication: concise writing and clear storytelling for business partners. Fluent in English.
Nice to have
•    Prior corporate/enterprise experience.
•    Experience in life sciences, manufacturing, or operations analytics.
•    Familiarity with Microsoft 365 Copilot and the surrounding ecosystem.
•    Exposure to data governance 

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