Azure AI Technical Advisor Specialist Role - Blr / Hyd

Greetings!!!

Currently we have an urgent position for Azure AI Technical Advisor Specialist role with one of our projects, location based in Bangalore / Hyderabad.

Kindly find below the details for your Perusal.

Job Location                Bangalore / Hyderabad

Mode of Employment Permanent (Work Mode: Hybrid, weekly 2 days in office)

Shift ModeRotational Shift which includes night Shift as well.

Job Description:

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 efficiencyavoiding 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 startupsfocused 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.

SKILLS:

• Understanding of, or curiosity to ramp up on, Azure AI/ML infrastructure,…