Technical Advisor Specialist(AI)

Job description

Role Title: Technical Advisor Specialist(AI) Microsoft for Startups Founders Hub is a dynamic platform that supports founders from the moment they have an idea. As their startup grows, founders unlock new benefits and features that help them hit their technical milestones and tackle business challenges. Founders globally can sign up for Microsoft for Startups Founders Hub and start using market-leading AI tools and a suite of benefits tailor-made to their startup stage with no funding required. Microsoft Services help customers realize their full potential through accelerated adoption and productive use of Microsoft technologies. We are a global team of highly dedicated professionals who deliver world class services with partners, earning customer confidence, trust, and loyalty by improving the overall Customer and Partner Experience, serving as the customer most trusted advisors within Microsoft and driving customer-centric product improvement. Azure Technical Advisory support is a Microsoft services & support offering targeted at Microsoft for Startups Founders Hub startups. This is a customer-specialist facing role and would require the individual to act as the customer’s trusted Technical Advisor Specialist. RESPONSIBILITIES SUMMARY: **1. Startup Discovery & AI Readiness Assessment** - Lead **startup-focused discovery sessions** to understand the founder vision, product roadmap, customer use cases, and near-term GTM priorities. - Assess **AI readiness** across data availability, engineering maturity, cloud footprint, and cost constraints common to early-stage startups. - Help startups **identify high-impact AI use cases** that accelerate product differentiation, customer value, or operational efficiency—avoiding over-engineering. - Guide founders and engineering leaders on **when to use Copilot, Azure OpenAI, Azure AI services, or custom ML** , balancing speed, cost, and scalability. **2. AI Architecture Design for Startup Scale** - Design **lean, scalable AI architectures** using Azure OpenAI, Azure AI Studio, Azure ML, Cognitive Services, and Azure-native data platforms. - Define **MVP-first AI patterns** (RAG, prompt engineering, inference-only architectures) optimized for rapid iteration and fast customer validation. - Create **future-ready architecture** that allows startups to scale from pilot to production without rework as usage and customers grow. - Provide **architecture diagrams, reference patterns, and decision rationale** that startup teams can easily execute against. **3. Azure Credits, Quotas & Cost-Conscious AI Design** - Advise startups on **Azure credits usage strategy** , ensuring AI workloads are aligned to available funding and program entitlements. - Guide startups through **Azure OpenAI / GPU quota planning** , helping unblock capacity constraints and avoid design dead-ends. - Recommend **cost-optimized AI approaches** (model selection, inference strategies, batch vs real-time, caching, vector store design). - Help startups understand **unit economics of AI features** , connecting architecture decisions to burn rate and runway. **4. Hands-on Technical Advisory & PoCs** - Provide **hands-on advisory support** to startup engineering teams during build phases, not just high-level guidance. - Lead or review **proofs of concept (PoCs)** to validate AI feasibility, latency, cost, and user experience early. - Review startup implementations for **architecture soundness, security basics, and scalability risks** , offering pragmatic improvements. - Support integration of AI into **existing product stacks** (APIs, web apps, mobile apps, SaaS platforms). **5. Responsible AI, Security & Trust (Startup-Appropriate)** - Embed **Responsible AI principles** in a way that is practical for startups—focused on trust, transparency, and customer confidence. - Advise on **data handling, PII protection, and secure model access** , especially for startups entering enterprise or regulated markets. - Help startups prepare for **enterprise customer security reviews** by aligning early with Azure and Microsoft security best practices. **6. Enablement & Founder / Team Upskilling** - Upskill startup teams on **Azure AI services, OpenAI patterns, and production-ready AI design** through working sessions and reviews. - Share **reusable reference architectures, templates, and best practices** to accelerate repeatable AI delivery. - Support creation of **internal AI standards or lightweight AI governance** as startups mature. - Act as a **long-term technical advisor** , helping startups evolve their AI approach as product-market fit and scale change. **7. Microsoft for Startups Program Alignment** - Align AI architecture recommendations with **Microsoft for Startups goals** : faster Azure adoption, sustainable scale, and long-term customer success. - Collaborate with **Microsoft account teams, program managers, and partners** to unblock startups and maximize program value. - Provide **clear, outcome-focused summaries** for internal stakeholders highlighting progress, risks, and next advisory actions. - Identify **patterns, blockers, and common challenges** across startups to help improve program effectiveness. **How this role is distinct in Microsoft for Startups** Compared to enterprise AI architects, this role is: - **More hands-on, less theoretical** - **Cost- and credit-aware** - **MVP- and speed-focused** - **Founder- and product-centric** - **Designed for rapid iteration, not long transformation cycles** SKILLS: - Understanding of, or curiosity to ramp up on, Azure AI/ML infrastructure, platform, and AI/ML services on L200-300 level: - Infrastructure planning for running and Finetuning LLM’s on managed compute. - Performance optimization techniques for inferencing workloads. - Integration of Azure ML with data Analytics platforms like Azure Synapse analytics or