Sr Backend Engineer
New
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Lead architecture and technical strategy for large-scale distributed systems powering business data platforms, AI services, and enterprise applications. Requires a bachelor's degree in computer science and eight years of software engineering experience coding in languages like C#, Java, Python, or C++. Deep expertise needed in distributed systems, cloud infrastructure, data platforms, AI-native development, and enterprise software. Base pay ranges from $165,600 to $296,400 annually, or $220,800 to $331,200 in San Francisco Bay Area and New York City.
Written from this posting by Neural Jobs AI. The full description is below.
The Microsoft Dataverse Intelligence Platform organization is building the next generation AI-native business data and intelligence platform for Microsoft. Our mission is to help customers turn enterprise data, business knowledge, and operational processes into actionable intelligence that powers copilots, agents, business applications, and autonomous workflows.
We build and operate the intelligent foundations that connect business data, semantic understanding, governance, analytics, process intelligence, and AI-powered execution at cloud scale. Our platform powers Microsoft Dynamics 365, Power Platform, Copilot experiences, and thousands of customer solutions worldwide. We enable organizations to securely transform business data into intelligence, intelligence into action, and action into measurable business outcomes.
As AI reshapes how software is built and how businesses operate, we are investing deeply in AI-native platforms, intelligent data systems, agent orchestration, enterprise governance, and hyperscale infrastructure that will power the next generation of business applications.
We are hiring for a Principal Software Engineer role within our Dataverse Intelligence Platform organization. These roles span several high-impact engineering areas, including:
AI-native business applications and intelligent agents
Business data platforms and semantic intelligence
Process Intelligence and AI-powered automation
Enterprise knowledge, retrieval, and grounding systems
Distributed systems, cloud infrastructure, and platform engineering
AI-native developer experiences and platform services
In these roles, you will provide technical leadership across complex, interconnected platform systems that serve millions of users and power mission-critical business processes worldwide. You will help define platform strategy, drive architecture, modernize services, advance AI-native engineering practices, and influence technical direction across multiple product areas.
Whether your background is in distributed systems, large-scale data platforms, AI infrastructure, retrieval and grounding systems, enterprise software, business applications, cloud services, or production AI systems, you will have the opportunity to shape the future of Microsoft's AI-powered business platform.
You will partner closely with engineering, product, research, data science, security, and business teams to solve ambiguous technical challenges, build durable platform capabilities, and deliver customer impact at global scale.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Lead architecture, technical strategy, and design for large-scale business data, intelligence, AI, and cloud platform systems. Define and drive technical direction across foundational platform capabilities, intelligent services, and cross-organization initiatives.
Design and evolve cloud-native distributed systems that power enterprise-grade business applications, data platforms, copilots, agents, and AI-driven experiences with a focus on scalability, reliability, performance, security, governance, compliance, and operational excellence.
Lead the development of AI-native platform capabilities, including enterprise retrieval and grounding systems, semantic intelligence, process intelligence, agent orchestration, intelligent automation, and LLM-powered experiences.
Drive the evolution of Dataverse as the business data and intelligence platform for the AI era, enabling customers to transform enterprise data, processes, and knowledge into actionable intelligence and business outcomes.
Champion AI-native engineering practices across the organization by leveraging AI throughout the software development lifecycle, accelerating innovation, improving developer productivity, and raising engineering quality.
Define platform architecture and modernization strategies that improve platform consistency, extensibility, resiliency, developer experience, and long-term maintainability across Microsoft's business application ecosystem.
Partner with engineering leaders, product managers, architects, researchers, data scientists, and business stakeholders to shape roadmaps, influence investments, and deliver platform capabilities that unlock customer and business value.
Evaluate architectural tradeoffs across data platforms, intelligence layers, AI systems, and distributed services while balancing customer needs, platform scalability, governance, cost efficiency, and long-term technical sustainability.
Establish reusable platform patterns, frameworks, APIs, data models, and intelligence services that enable teams across Microsoft to build AI-powered solutions faster and with higher quality.
Champion engineering excellence through secure development practices, automation, CI/CD, observability, testing, telemetry, incident management, and operational rigor for mission-critical cloud services.
Mentor and develop engineers through technical leadership, architecture reviews, design coaching, AI-native engineering best practices, and leadership by example.
Foster a culture of customer obsession, innovation, accountability, continuous learning, and inclusive collaboration while helping teams navigate ambiguity and deliver impact at scale.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Preferred Qualifications:
#AgenticDataplatform #AINative #Dataverse #AIBusinessApplication
Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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Microsoft builds Windows, Azure, Office and the Copilot family of AI assistants, and operates one of the largest AI training and inference fleets in the world. Microsoft Research and the AI platform teams work across foundation models, systems for large-scale training, and applied ML in every product line.
Founded in 1975 and headquartered in Redmond, Washington, the company is also OpenAI's principal compute partner and ships AI tooling for developers through GitHub, VS Code and Azure AI.
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