Sr. Principal, Infra services AI and Agentic specialist

External

Ntrs · Pune, India

Full-timeHybridToday

AzureCI/CDFastAPIFlaskIncident ResponseIntegration Testing

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About the role

As part of our Infrastructure Services team, you will build / implement production-grade AI and machine learning solutions that improve infrastructure engineering and operations. This is a hands-on engineering role focused on designing, developing, integrating, and operating AI-powered capabilities that drive automation, resilience, observability, and service efficiency across a complex enterprise infrastructure estate. As an Applied AI/ML Engineer within Infrastructure Services, you will work closely with infrastructure engineering, operations, platform, security, and product teams to deliver AI-enabled solutions that solve real operational problems. You will build and maintain backend services, AI workflows, copilots, retrieval and orchestration pipelines, and automation components using modern Python-based engineering practices and Azure AI services. The role requires strong software engineering fundamentals, experience integrating LLM and ML capabilities into enterprise systems, and the ability to take solutions from prototype to production with proper testing, observability, governance, and lifecycle management.

Responsibilities

Design, build, and deploy AI-powered applications, services, and automation workflows for infrastructure operations using Python, APIs, and cloud-native engineering patterns.

Develop LLM-based copilots, agentic workflows, and retrieval-augmented solutions that support incident response, knowledge discovery, operational triage, service requests, and engineering productivity.

Build and integrate AI components using frameworks and services such as LangChain, LangGraph, Azure AI Foundry, Copilot Studio, and related Azure AI capabilities, based on solution fit and enterprise standards.

Engineer robust backend services and APIs using Python, FastAPI, Flask, and data-processing libraries to connect AI solutions with infrastructure platforms, operational tools, and enterprise data sources.

Own the end-to-end software delivery lifecycle, including solution design, coding, code reviews, unit testing, integration testing, deployment, release management, and production support.

Implement observability, tracing, logging, evaluation, and performance monitoring to ensure AI solutions are reliable, measurable, debuggable, and supportable in production.

Partner with infrastructure SMEs, operations teams, and product stakeholders to translate operational problems into scalable AI and automation solutions with clear business and engineering outcomes.

Apply engineering best practices for secure and responsible AI, including access controls, data handling, governance, guardrails, prompt and workflow design, and operational risk management.

Optimize solutions for latency, throughput, quality, and cost, and continuously improve them based on production telemetry, user feedback, and evolving business priorities.

Collaborate effectively with global engineering teams to deliver reusable platforms, shared services, and production-ready AI capabilities across multiple infrastructure domains.

Required Qualifications, Capabilities, and Skills

15+ years of experience in enterprise technology, infrastructure engineering, or automation, with at least 5+ years of hands-on experience designing and building AI/ML or GenAI solutions for real-world business or operational use cases.

Strong understanding of enterprise infrastructure across compute, storage, networking, identity, observability, and operations in hybrid and multi-cloud environments.

Hands-on experience with AI orchestration and application frameworks such as LangChain, LangGraph, Semantic Kernel, or similar frameworks for building production AI workflows and agentic systems.

Hands-on experience with Microsoft AI platforms and services such as Azure AI Foundry, Azure OpenAI, Copilot Studio, and related Azure services used to develop, secure, and operationalize enterprise AI solutions.

Strong software engineering background with proficiency in Python and practical experience with FastAPI, Flask, Pandas, REST APIs, testing frameworks, version control, and CI/CD practices.

Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent practical experience; experience with TensorFlow, model integration patterns, evaluation frameworks, and production observability is a strong adva

Sr. Principal, Infra services AI and Agentic specialist

About the role

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Company Intel

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