Technology Specialists Azure Ai Services/azure Open

il y a 1 mois

Paris, France Microsoft Temps plein

This role sits in our Global Black Belt (GBB) organization, which is a team of highly specialized and technical professionals within our Microsoft Customer & Partner Solutions organization (MCAPS) who work with customers to enable some of the most complex and innovative solutions, providing differentiated technical leadership and guidance along the way. The AI team within the GBB organization consists of Specialist and Technology experts, who focus on specific domains, industries, and workloads, such as Azure OpenAI Service, Azure AI Services, Application Development and Machine Learning.

This role will require travel to customer sites.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

**Responsibilities**:

- ** Provide in-depth AI expertise** to support the technical relationship with Azure customers, including product and solution briefings, creating demos, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Azure AI Services (Cognitive services portfolio, Azure Open AI).
- **Support** developers, creators, and enterprises to leverage Speech, Vision, Text, Search, Azure Open AI APIs so they can build their own AI products in the future.
- **Demonstrate** how Azure AI is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and benchmarking.
- **Build** repeatable assets to enable other customers and internal teams.
- **Influence** Azure AI strategy by leveraging Cognitive Services, Search and Azure Open AI models by advocating enterprise customer requirements.
- **Address** security and IP, performance, scalability, and customer readiness
- **Engages** in conversation with customers and collaborates with account and partner teams to drive and qualify new opportunities, understand key technical objections, and resolve technical blockers.
- **Identifies** customer business and technology readiness, proactively builds external stakeholders' mapping, implements strategies to accelerate the closing of deals, contributes input on strategies to drive and close prioritized opportunities, coaches junior team members in deal plan execution, and implements close plans.

**Qualifications**:
**Required/Minimum Qualifications**:

- 8+ years of technical pre-sales or technical consulting experience
- OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 6+ years of technical pre-sales or technical consulting experience
- OR Master's Degree in Computer Science, Information Technology, or related field AND 4+ years of technical pre-sales or technical consulting experience
- OR equivalent experience.
- **AI Experience**: 3+ years of AI (Machine Learning, Intelligent Apps/Agents, Search) selling experience in enterprise public cloud-based solutions. Technical expert on AI/Cognitive Services.
- **Solution Sales Experience**: 3+ years in customer-facing advisory or pre-sales to demonstrate the ability to distill core technical concepts and connect them to business outcomes.

**Additional or Preferred Qualifications**:

- Experience and skills with Azure Data and AI services or equivalent compete experience.
- Knowledge of the AI open-source ecosystem.
- Strong knowledge of Cognitive Services, Azure Cognitive Search and Azure Open AI (including Speech, Vision, Translation etc.) or equivalent compete experience.
- Knowledge of Prompt Engineering, LLM fine turning, and chaining technology (e.g., LangChain, Semantic Kernel) expertise.
- Knowledge of large language model (LLM) and Foundational models toolsets
Experience with implementing Retrieval Augmented Generation (RAG) architectures.

GBBAIFY24H1

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