Technology Specialist

3 semanas atrás

Sao Paulo, Brasil Microsoft Tempo inteiro

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**:

- 6+ years of technical pre-sales or technical consulting experience
- OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years of technical pre-sales or technical consulting experience
- OR Master's Degree in Computer Science, Information Technology, or related field AND 3+ years of technical pre-sales or technical consulting experience
- OR equivalent experience.
- ** AI Experience**: 3+ years of cloud based AI technical solutions development including, but not limited to, any of the following: Azure Cognitive Services; AI Voice Assistants; AI Chatbots; AI Image Recognition and Computer Vision, AI Natural Language Processing; AI Recommendation Systems; AI Sentiment Analysis; AI Virtual Realty; AI Autonomous Systems; AI Healthcare Applications; or AI Data Analytics and Predictive Modeling and technical selling in enterprise public cloud-based solutions.

**Additional or Preferred Qualifications**:

- Experience and skills with Azure Data and AI services or equivalent compete experience.
- Knowledge of the AI open-source ecosystem
- Excellent 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.

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