M

Microsoft

Builds workplace software, PCs and cloud services

Senior Consultant - Full Stack Apps

AI Application Engineering +1Posted on Nov 11
Full-timeNo salary listedIn-person

About the Job

Requirements

  • 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; advanced or higher-education qualifications are a plus.
  • 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 cross-cutting concerns such as logging, security, resiliency, and configuration management.
  • Hands-on experience with multithreaded and parallel programming and high-throughput service design.
  • Strong hands-on experience with Azure AI Foundry, Azure AI Search, Cognitive Search, Vector Search, and Retrieval-Augmented Generation patterns is preferred.
  • Expertise building enterprise-grade large language model and agentic AI solutions using Semantic Kernel, LangChain, LangGraph, AutoGen, and developer copilots such as GitHub Copilot and Cursor.
  • Practical experience in prompt engineering, prompt optimization, evaluation frameworks, and reliability tuning to deliver safe, high-quality AI outputs.
  • Advanced Python expertise implementing Retrieval-Augmented Generation pipelines, vector workflows, agent orchestration, and AI evaluation frameworks.
  • Strong understanding and application of Responsible AI principles, including safety, fairness, transparency, and governance; this is mandatory.
  • 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 and dynamic application security testing, and secure continuous integration and delivery pipelines.
  • Familiarity with security and monitoring tools such as 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.
  • Architectural breadth through exposure to open-source technologies and platforms, and good exposure to Azure, AWS, or Google Cloud Platform, along with industry experience across financial services, government, healthcare, manufacturing, or retail and supply chain.

Responsibilities

  • Lead technical delivery of complex, cloud-native and AI-enabled engagements as a hands-on individual contributor, and lead engineering teams when required to ensure high-quality, predictable outcomes.
  • Define and drive technology strategy for large and complex customer engagements, ensuring solutions are scalable, secure, and aligned with business objectives, architectural best practices, and Microsoft reference architectures.
  • Design, develop, and deploy solutions on Microsoft Azure, accelerating customer value through 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 for 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 AI solutions with strategic customers.
  • Contribute to thought leadership and continuous improvement, fostering ways of working that enhance engineering productivity, solution quality, and responsiveness to customer needs.
  • Lead rapid prototyping, pilots, and early-stage production deployments for enterprise customers to accelerate time-to-value.
  • Translate ideas from whiteboard to production with minimal friction by engineering alongside customer teams to unblock delivery and adoption.
  • Own troubleshooting across performance, reliability, cost, security, and data quality, delivering outcome-driven engineering in ambiguous, high-pressure environments.

Desired Qualifications

  • Microsoft and cloud technology certifications are preferred, including AZ-204, AI-102, MCSD, MCSE, or equivalent modern cloud and AI certifications.
  • Experience with Azure AI Foundry, Azure AI Search, Cognitive Search, Vector Search, and Retrieval-Augmented Generation patterns is preferred.

About the Company

Microsoft

Builds workplace software, PCs and cloud services

Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Redmond, WA
Founded
1975

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