Full-Time
Senior Consultant
Dotnet Full stack + AI
Posted on 8/18/2026
Microsoft
10,001+ employees
Develops software, OS, and cloud services
No salary listed
Hyderabad, Telangana, India + 2 more
More locations: Noida, Uttar Pradesh, India | Bengaluru, Karnataka, India
In Person
Bachelor's
 Software Engineering (1) |
|---|
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- At least 10 years of overall professional experience in software engineering, application development, and solution delivery, with a strong focus on enterprise-scale, customer-facing engagements.
- At least 5 years of experience in customer-facing delivery leadership.
- A Bachelor's degree in computer science engineering or a related field.
- Strong experience designing, building, and deploying business- and mission-critical applications using .NET (C#), .NET Web APIs, and Node.js.
- Full-stack development expertise across UI, API, service, domain, data, and integration layers, with proficiency in C#, JavaScript, TypeScript, Angular or React, HTML5, and CSS/SCSS.
- Deep understanding of software architecture patterns and anti-patterns for large-scale systems, including MVC, CQRS, and Saga, with a focus on performance, scalability, and resiliency.
- A strong foundation in software engineering principles, data structures, algorithms, testing, debugging, and analytical problem-solving.
- Proficiency with cloud data platforms including Azure SQL, Cosmos DB, Azure Database for PostgreSQL, MySQL, Azure SQL Managed Instance, and MariaDB.
- Experience creating reusable application frameworks and shared components addressing logging, security, resiliency, and configuration management.
- Hands-on experience with multithreaded and parallel programming and high-throughput service design.
- Proven expertise building enterprise-grade large language model and agentic artificial intelligence solutions using Semantic Kernel, LangChain, LangGraph, AutoGen, GitHub Copilot, and Cursor.
- Practical experience in prompt engineering, prompt optimization, evaluation frameworks, and reliability tuning for safe, high-quality artificial intelligence outputs.
- Advanced Python expertise implementing retrieval-augmented generation pipelines, vector workflows, agent orchestration, and artificial intelligence evaluation frameworks.
- Strong understanding and application of Responsible Artificial Intelligence principles, including safety, fairness, transparency, and governance.
- Extensive experience designing, implementing, operating, tuning, and troubleshooting large-scale cloud solutions on Microsoft Azure or another public cloud.
- Hands-on expertise implementing microservices and serverless architectures using Kubernetes, Azure Functions, Service Fabric, and related platforms.
- Strong experience defining and implementing continuous integration and continuous delivery pipelines, automated testing, and release strategies including blue-green and canary deployments.
- Deep experience with cloud monitoring and end-to-end telemetry to ensure observability, reliability, and production readiness.
- Strong expertise in security-by-design principles, including encryption, authentication, and authorization.
- Deep knowledge of Zero Trust architecture, identity and access management, secure-by-default design, threat modeling, compliance standards, and DevSecOps practices.
- Hands-on experience with least-privilege access, assume-breach concepts, micro-segmentation, continuous monitoring, static application security testing, dynamic application security testing, and secure continuous integration and continuous delivery pipelines.
- Familiarity with Microsoft Defender for Cloud, Microsoft Threat Modeling Tool, Azure Sentinel, and Splunk.
- Proven experience delivering large-scale digital transformation initiatives, including cloud migration and hybrid modernization programs.
- Exposure to open-source technologies and platforms, Azure, Amazon Web Services, and Google Cloud Platform.
- Industry experience across financial services, government, healthcare, manufacturing, and retail or supply chain.
- The ability to lead rapid prototyping, pilots, and early-stage production deployments for enterprise customers.
- The ability to translate from whiteboard to production while engineering alongside customer teams to unblock delivery and adoption.
- The ability to own troubleshooting across performance, reliability, cost, security, and data quality in ambiguous, high-pressure environments.
- Lead the technical delivery of complex, cloud-native and artificial-intelligence-enabled engagements as a hands-on individual contributor and, where required, lead engineering teams to ensure high-quality, predictable outcomes.
- Define and drive the technology strategy for large and complex customer engagements, ensuring solutions are scalable, secure, aligned to business objectives, and consistent with architectural best practices and Microsoft reference architectures.
- Design, develop, and deploy solutions on Microsoft Azure using Microsoft technologies, platforms, and delivery methodologies.
- Apply user-centered design principles to translate customer needs into clear technical requirements and scalable solution designs through iterative prototyping and feedback.
- Provide delivery leadership by setting technical priorities, estimating effort, managing dependencies, making disciplined trade-offs, and driving successful releases.
- Ensure engineering excellence and solution quality, with accountability for the efficacy, performance, security, and compliance of technical delivery within assigned engagements.
- Identify, assess, and manage technical risks and dependencies across projects, including defining mitigation strategies, handling escalations, and planning short- and long-term delivery risks.
- Apply information security, compliance, and assurance standards to maintain stakeholder confidence and meet customer, regulatory, and Microsoft governance requirements.
- Drive innovation and digital transformation by leveraging existing intellectual property, reusable assets, and best practices to improve delivery predictability and speed.
- Collaborate with Sales, account-aligned teams, and peers to articulate technical value propositions and support expansion and adoption of Microsoft cloud and artificial-intelligence solutions with strategic customers.
- Contribute to thought leadership and continuous improvement by fostering ways of working that enhance engineering productivity, solution quality, and responsiveness to evolving customer needs.
- Microsoft and cloud technology certifications, including AZ-204, AI-102, MCSD, MCSE, or equivalent modern cloud and artificial-intelligence certifications.
- Experience with Azure AI Foundry, Azure AI Search, Cognitive Search, Vector Search, and retrieval-augmented generation patterns.
Microsoft develops software, devices, and cloud services. Windows is an operating system that runs on personal computers, Office provides productivity apps, and Azure offers cloud computing and developer tools. The company differentiates itself with a large, integrated ecosystem of software, devices, and services, plus long-standing partnerships with PC makers and a broad enterprise footprint. Its goal is to put a computer on every desk and in every home, and to extend that reach through cloud services, professional networking (LinkedIn), and gaming.
Company Size
10,001+
Company Stage
IPO
Headquarters
Redmond, Washington
Founded
1975
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Simplify's Take
What believers are saying
- Fiscal 2026 revenue reached $331.8 billion, up 18%, with strong operating leverage.
- Azure crossed $100 billion annual revenue in fiscal 2026, while growing 43% year over year.
- Microsoft 365 Copilot passed 30 million paid seats, proving enterprise willingness to pay.
What critics are saying
- July 23, 2026 Azure maintenance bug broke Copilot, Teams, Graph, and Microsoft 365 globally.
- July 6, 2026 Microsoft cut 4,800 jobs, including 3,200 Xbox roles, signaling internal strain.
- OpenAI supplies roughly 70% of Microsoft AI revenue, creating concentration and dependency risk.
What makes Microsoft unique
- July 29, 2026: Microsoft commercial backlog hit $678 billion, locking in future revenue.
- Office, Windows, and Azure create unmatched distribution across work, devices, and cloud.
- Microsoft Foundry and Copilot bundle models, apps, and commerce into one enterprise platform.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
401(k) Company Match
Professional Development Budget
Conference Attendance Budget
Flexible Work Hours
Remote Work Options
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -1%2 year growth
↑ 0%Investor sentiment around artificial intelligence is shifting towards demanding concrete returns rather than just ambitious spending promises. Tech companies plan to invest over $700 billion in AI this year, with expectations of further increases. Recent earnings revealed a clear divide. Microsoft, Amazon, and Palantir saw double-digit stock price jumps after demonstrating strong results. Microsoft maintained $19.9 billion in quarterly free cash flow despite heavy AI investments, whilst Amazon's cloud division posted its fastest growth in four years, with its AI business exceeding a $25 billion annual run rate. Meanwhile, Meta Platforms, Alphabet, and Tesla faced investor scepticism over their substantial AI expenditures without comparable proof of returns. The market has entered what analysts call the "show me" phase, where tangible financial results from AI investments now matter more than spending commitments alone.
Microsoft reported a $678 billion commercial backlog and Azure surpassing $100 billion in annual revenue, growing 41%. The company posted fiscal 2026 revenue of $331 billion, up 18%, with Q4 non-GAAP EPS of $4.74 beating consensus by 11.81%. Microsoft 365 Copilot reached over 30 million paid seats, with net seat additions more than doubling quarter over quarter. Azure guidance implies approximately 45% constant-currency growth in Q1 FY27. However, full-year capital expenditure hit $115.95 billion, up 79.62%, while free cash flow fell to $66.99 billion, down 6.46%. The company's OpenAI investment resulted in $3.1 billion in Q1 FY26 losses. Shares are up 21.2% over the past month but roughly flat year to date. Analysts cite the recurring revenue backlog as a key differentiator in the AI market.
Goldman Sachs estimates $7.6 trillion in cumulative AI capital spending from 2026 through 2031, whilst OpenAI and Anthropic generated combined annualised revenue exceeding $105 billion by August 2026. The industry must scale annual recurring revenue past $1 trillion by 2030 to avoid infrastructure write-downs on hardware with 3-to-5-year lifecycles. Nvidia faces exposure as its 74.9% quarterly gross margin depends on scarce GPU demand, whilst hyperscalers deploy internal chips like Google's TPUs and Amazon's Trainium. The shares traded at 25.64 times forward earnings as of 17 August. Microsoft's AI operations exceeded a $37 billion annual run rate in the March quarter, up 123% year-on-year. GPT-4-level inference costs have fallen 50-fold, potentially expanding market demand.
Microsoft Advertising released an agentic commerce blueprint on Friday to help businesses prepare for AI agents making purchases on behalf of consumers. The "Agentic Playbook" focuses on three priorities: ensuring brands get discovered by agents, making purchases seamless, and optimising performance. The blueprint outlines a 90-day implementation structure. The first 45 days focus on building foundations like preparing product feeds and ensuring smooth checkout. The second 45 days concentrate on content optimisation. Bain & Company estimates agentic commerce will account for 15% to 25% of the US e-commerce market by 2030. Microsoft Copilot operates on the Universal Commerce Protocol, connecting it with retailers including Target and Ulta Beauty. On Thursday, Microsoft rolled out AI Max to all accounts, offering features like search term matching and dynamic URL routing for advertising campaigns.
ChronoScale has entered a two-year strategic partnership with Microsoft to deploy approximately 50 MW of AI compute capacity, the company disclosed in its annual report filed Wednesday. The project will use NVIDIA GB300 systems with advanced liquid cooling for high-density AI workloads, with completion targeted for the first quarter of 2027. The deployment remains subject to financing and meeting various development milestones. ChronoScale reported $9.7 million in cash and a $42.6 million working-capital deficit as of 31 May. The company has access to a $100 million promissory note from parent firm Applied Digital, with $93 million undrawn. ChronoScale reported fiscal 2026 revenue of $71.6 million, down 15% year-on-year, primarily due to a customer loss in December 2024. Operating loss narrowed to $37.5 million from $55.3 million.