Cloud Architecture

Sonata Software Overview

In today's market, there is a unique duality in technology adoption. On one side, extreme focus on cost containment by clients, and on the other, deep motivation to modernize their Digital storefronts to attract more consumers and B2B customers.

As a leading Modernization Engineering company, we aim to deliver modernization-driven hypergrowth for our clients based on the deep differentiation we have created in Modernization Engineering, powered by our Lightening suite and 16-step Plat formation™ playbook. In addition, we bring agility and systems thinking to accelerate time to market for our clients.

Headquartered in Bengaluru, India, Sonata has a strong global presence, including key regions in the US, UK, Europe, APAC, and ANZ. We are a trusted partner of world-leading companies in BFSI (Banking, Financial Services, and Insurance), HLS (Healthcare and Lifesciences), TMT (Telecom, Media, and Technology), Retail & CPG, and Manufacturing space. Our bouquet of Modernization Engineering Services cuts across Cloud, Data, Dynamics, Contact Centers, and around newer technologies like Generative AI, MS Fabric, and other modernization platforms.

Job Title : Cloud Solution Architect (CSA)

Job Title : Hyderabad / Bangalore

Role Description :

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 advocates within Microsoft and driving customer-centric product improvement.

We are seeking an experienced Azure AI Consultant to join our team. The ideal candidate will have a strong background in Azure cloud computing and AI technology. The candidate will be responsible for implementing Azure Open AI solutions for clients, providing technical guidance, and delivering high-quality solutions.

RESPONSIBILITIES SUMMARY :

Have technical discussions with the customer with a discovery mindset, understanding their use-case, technical infrastructure, cloud infrastructure, ML tooling and future goals.

Digest the information on a product feature scope and document, share and plan future advisories from here.

Assist on compute on both levels – planning for current optimal usage and future scope, as well as getting those allocated through the available and pre-decided channels.

Advise startups on blockers for scenarios – not restricted to but including cost optimization of ML workloads, optimal use of infrastructure, right way of fine-tuning or inferencing on ML platform.

Advise startups proactively on features and open-source software supported by Azure that the startup can think about for their current infrastructure.

Provide reporting on the above on a weekly basis and ensure project management independently.

Be able to take decisions or escalate matter suitably, as per the needs of the account.

Guide fellow advisors on topics they’d need help with.

• Design and implement Azure Open AI solutions for clients

Provide technical guidance and advice to clients

Work closely with clients to understand their requirements and objectives

Develop custom solutions to meet client needs

Conduct training sessions for clients

Identify areas for improvement and propose solutions

Participating in the development of proposals

Keep up to date with the latest Azure and Open AI technologies and trends

Work collaboratively with other members of the team to deliver high-quality solutions

Skills

Understanding of, or curiosity to ramp up on, Azure AI infrastructure, platform, and services on L300-400

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 L400 and consult with startups about fine-tuning, simple prompt engineering 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.

Ideal Experience