Technical Advisor Specialist(AI)

Sonata Software; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Sonata Software in Hyderabad, India, seeks a Technical Advisor Specialist (AI) to guide startups in adopting Azure AI and OpenAI, designing MVP-first architectures, and leading PoCs for rapid validation.

You will ensure Responsible AI, data security, and scalable integration with client stacks while enabling founders through hands-on advisory and best practices across Azure services.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 12+ years of Azure cloud computing experience and 3+ years in OpenAI technology.
• Proficiency in Python, C#, Java and SQL.
• Azure certifications (AZ-104, AZ-305, AI-102) preferred.

Responsibilities

• Lead startup-focused discovery sessions to understand founder vision and AI readiness.
• Design lean, scalable AI architectures using Azure OpenAI and Azure ML.
• Lead or review proofs of concept (PoCs) to validate AI feasibility, latency, cost, and UX.
• Embed Responsible AI, data handling, and secure model access in startup guidance.
• Enable founders and teams with training and reusable reference architectures.

Skills

Azure AI/ML infra

Infrastructure planning

Model inference optimization

RAG & prompt engineering

Azure OpenAI / GPU planning

ML framework proficiency

Education

Bachelor's degree in Computer Science or related field

Tools

TensorFlow

PyTorch

Azure ML

Cognitive Services

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.
• 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 Databricks.
• Designing Recommendation/personalization models.
• Implementing observability and monitoring on Azure AI/ML services.
• Deep understanding of Azure services (Azure Machine Learning, Azure Cognitive Services, Azure Synapse Analytics/Databricks, etc.) and building solutions around these services.
• Proficiency in AI and ML frameworks and tools (TensorFlow, PyTorch, Scikit‑learn, etc.).
• Good understanding of frameworks like Semantic Kernel, Autogen, Langchain and protocols like MCP and Agent to Agent.
• Good understanding of data engineering and ETL processes.
• Experience of having handled ML specific requests and/or solution build for startups
• Ability to understand and deep dive on ML pipeline, ML Ops and data ingestion as it refers to Azure ML.
• Ability to gear up on applied AI services like Azure OpenAI Service on L300 and consult with startups about RAG, fine‑tuning, prompt engineering, building Agentic systems etc.
• Ability to understand the magnitude of ML pipeline in terms of data set size, intensive training, computing involved etc, to have a planning discussion with the startup.
• Ability to carry out weekly discussions and report on highs, lows and blockers.

Requirements:

• Bachelor's degree in Computer Science or a related field
• Minimum of 12+ years of experience in Azure cloud computing and 3+ years in Open AI technology
• Experience in designing and implementing solutions using Azure AI services
• Strong understanding of Azure cloud services, including Azure Machine Learning and Cognitive services
• Proficiency in programming languages such as Python, C#, and Java and Proficiency in SQL
• Excellent problem‑solving skills and ability to think creatively
• Strong communication skills and ability to work with clients
• Ability to work independently and in a team environment
• Relevant Azure certifications preferred (AZ-104, AZ-305, AI‑102, AB‑730 & AB‑731 certification, preferred)