Job Overview

Microsoft is hiring a Senior Software Engineer in Hyderabad to help shape intelligent enterprise systems within Microsoft Digital and the Infrastructure Engineering Services organization. This senior individual contributor position focuses on artificial intelligence, agentic systems, cloud-native engineering, distributed applications, and enterprise AIOps.

The engineer will help create a Unified AIOps Platform that brings together AI agents, tools, workflows, applications, automation capabilities, and operational intelligence into a scalable ecosystem. The role combines hands-on software development with architecture ownership and technical leadership. You will work with product managers, architects, data scientists, security specialists, and business stakeholders to turn complex AI opportunities into production-ready solutions.

This opportunity is particularly relevant to experienced engineers who have built enterprise-scale AI products and understand the full journey from experimentation and architecture through deployment, monitoring, governance, and continuous improvement.

Key Responsibilities

• Act as a senior technical authority for AI engineering, helping teams make sound decisions across architecture, development, delivery, and operations.
• Define technical direction for complex AI-powered products, platforms, and enterprise automation scenarios.
• Research emerging AI models, frameworks, development patterns, and technologies and evaluate their practical value.
• Use experimentation, prototypes, technical analysis, and data to resolve ambiguous engineering problems.
• Establish reusable AI engineering patterns, reference architectures, frameworks, and development standards.
• Lead architecture and design reviews for complex AI systems and influence decisions across multiple engineering teams.
• Design and develop a unified AIOps platform that connects independent tools, services, AI agents, skills, workflows, and automation capabilities.
• Create common patterns for orchestration, system integration, agent-to-agent communication, identity, data management, observability, and governance.
• Build a flexible architecture that allows new agents, tools, skills, and services to be onboarded, discovered, orchestrated, and reused efficiently.
• Remain hands-on with software architecture and implementation while guiding technical alignment across contributing teams.
• Improve the scalability, reliability, security, performance, and operational efficiency of AI-powered enterprise systems.

Required Skills

Candidates should have at least 10 years of hands-on software engineering experience, including significant work designing, developing, and delivering enterprise-scale cloud-native applications and distributed systems.

Strong programming experience is expected in one or more languages such as C, C++, C#, Java, JavaScript, or Python. The role also requires broad full-stack engineering knowledge covering frontend development, backend services, APIs, microservices, cloud platforms, data engineering, and modern application architecture.

A strong background in production AI is essential. Relevant experience includes Generative AI, Large Language Models, AI agents, agentic AI, multi-agent systems, retrieval-augmented generation, semantic search, vector databases, and workflow orchestration.

The successful candidate should understand the AI lifecycle, including model selection, fine-tuning, evaluation, prompt engineering, inference optimization, safety validation, deployment, monitoring, and ongoing production management.

Required Technologies

The role involves a broad modern technology stack. Relevant technologies and platforms include C#, .NET, Python, React, Angular, TypeScript, REST, GraphQL, Microsoft Azure, microservices, event-driven architectures, CI/CD, telemetry, monitoring, and distributed systems.

AI technologies and frameworks mentioned for the position include Microsoft Agent Framework, Semantic Kernel, Azure AI Foundry, Azure OpenAI, Copilot Studio, MCP, LangChain, LangGraph, AutoGen, CrewAI, OpenAI, and Anthropic. Experience with equivalent AI frameworks may also be relevant when supported by strong technical judgment.

Experience with RAG, semantic search, vector databases, agent orchestration, AI evaluation, observability, guardrails, Responsible AI, authentication, authorization, and production governance is highly relevant.

Preferred Skills

A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline is preferred. Additional value comes from experience with Responsible AI, compliance, privacy, enterprise security, governance, and operational requirements.

Experience designing evaluation and quality frameworks for AI agents, including observability, reliability measurement, and performance tracking, can strengthen an application. Exposure to networking, infrastructure, telemetry, large-scale operational systems, AIOps, monitoring, and operational intelligence is also desirable.

Soft Skills

This is a senior technical leadership position that requires excellent communication and collaboration. The engineer should be able to explain complex AI and architecture concepts to both technical and business audiences.

Strong analytical thinking, problem-solving, ownership, curiosity, and decision-making are important. The role requires influencing teams without relying on direct organizational authority, mentoring engineers through design and code reviews, and building alignment across diverse stakeholder groups.

The ability to work with Product Managers, Architects, Applied Scientists, Security teams, and executive stakeholders is particularly important. Candidates should be comfortable leading technical discussions and representing engineering viewpoints in architecture reviews and cross-functional initiatives.

Education

The required education is a Bachelor's degree in Computer Science or a related technical field, together with the required professional engineering experience. Equivalent practical experience is also accepted. A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is preferred.

Experience

The position requires 10+ years of hands-on software engineering experience. Candidates should have a strong record of designing and delivering enterprise-scale cloud-native applications and distributed systems.

Significant production experience with Generative AI, LLMs, AI agents, RAG, semantic search, vector databases, agentic systems, and AI workflow orchestration is expected. Experience across software engineering, cloud platforms, full-stack development, AI infrastructure, security, observability, and production operations will be important for success.

Benefits of Working in this Role

This role provides an opportunity to work on enterprise AI and AIOps capabilities at significant scale. Engineers can contribute to systems that combine AI agents, automation, distributed services, operational intelligence, and cloud technologies.

The position also offers the technical scope to influence architecture, establish reusable engineering practices, work with modern AI frameworks, and solve challenging problems involving reliability, security, scalability, governance, and production AI operations.

Work Mode

The position follows a hybrid work model with 3 days per week in the office. Travel is listed as less than 25%.

Location

The role is based in Hyderabad, Telangana, India. It is relevant to professionals searching for Microsoft jobs in Hyderabad, Senior Software Engineer jobs, AI Engineer jobs, AIOps jobs, Generative AI jobs, Azure jobs, Agentic AI jobs, Cloud Software Engineer jobs, and enterprise software jobs.

Who Should Apply

This opportunity is designed for senior software engineers with extensive experience building enterprise-grade applications and distributed cloud systems. Applicants should have strong software engineering fundamentals combined with substantial practical experience delivering production AI solutions.

Professionals with backgrounds in AI platforms, AIOps, Generative AI, LLM applications, multi-agent systems, Azure, cloud-native architecture, microservices, RAG, vector databases, and AI orchestration should consider applying. The role is especially suited to senior individual contributors who enjoy remaining hands-on while influencing architecture and engineering strategy across multiple teams.

Career Growth

The position can support continued growth toward technical leadership in enterprise AI, AIOps, cloud architecture, distributed systems, AI platform engineering, and responsible AI. Its combination of hands-on development, architecture ownership, cross-team influence, and AI innovation provides a broad platform for deepening technical leadership expertise.

Application Advice

When applying, highlight projects where you designed and delivered production-scale AI or cloud-native systems. Explain your contribution to architecture, software development, deployment, reliability, and operational improvement rather than listing technologies alone.

Clearly showcase experience with Generative AI, LLMs, AI agents, RAG, vector databases, semantic search, model evaluation, prompt engineering, AI safety, and production monitoring where applicable. Mention relevant Azure services and frameworks such as Azure AI Foundry, Azure OpenAI, Semantic Kernel, or Microsoft Agent Framework if you have hands-on experience.

Also emphasize full-stack development, APIs, microservices, distributed systems, CI/CD, security, observability, governance, and cloud operations. Because this is a senior individual contributor role, demonstrate examples of technical ownership, architecture decisions, mentoring, design reviews, and influence across multiple teams.

The posting states that applications will remain open for a minimum of five days and will be accepted on an ongoing basis until the position is filled.