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# Principal AI Platform Engineer - Onsite

- **Company:** Cognizant Technology Solutions Corporation
- **Location:** San Leandro, CA, United States
- **Experience:** Expert
- **Salary:** $120,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** ASP.NET, .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Cloud Engineering, Code Review, Databases, Continuous Integration, Extract Transform Load (ETL), Distributed Systems, Supervisory Control and Data Acquisition (SCADA), Key Management, Systems Development Life Cycle, Software Tools, Search Technologies, Software Engineering, Digital Twin, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Generative AI, Agentic-AI, Event Driven Architecture, Build Management, AI Platforms, Kubernetes, Low Latency, Cloud Migration, Cloud Integration, Restful APIs, Industrial Software, Software Version Control, Api Management, Serverless Computing, Microservices
- **Published:** October 28, 2026
- **Apply:** https://dejobs.org/x/x/8122CBDB515945ADA9B997F4A206506A/job/

## About the Role

* Typically 10-15 years of relevant software engineering, AI, cloud/platform engineering, distributed systems, or industrial software experience.
 * Strong hands-on expertise in Applied AI and Generative AI, including production implementation of LLMs, RAG, agents, vector search, evaluation, grounding, safety, monitoring, latency, and cost management.
 * Strong backend engineering experience with C#, .NET, ASP.NET Core, APIs, microservices, containers, and Kubernetes.
 * Advanced hands-on experience across Azure and AWS, including compute, Kubernetes/containers, serverless, databases, storage, messaging, identity, secrets management, API management, monitoring, CI/CD, and Infrastructure as Code.
 * Experience with multicloud architecture and cloud migration, preferably including Azure-to-AWS migrations.
 * Understanding of industrial environments such as SCADA/OT, historians, MES, time-series data, ERP/EAM, digital twins, and edge/cloud integration.
 * Strong understanding of secure software engineering, testing, observability, deployment, scalability, performance, release readiness, and production support.
 * Ability to provide technical leadership and influence engineering teams without requiring direct people-management responsibility.

Highly Desirable

 * Experience designing and operating agentic AI systems that automate SDLC activities such as requirements analysis, coding, code review, testing, dependency upgrades, and release preparation.
 * Experience integrating AI agents with source control, CI/CD, and engineering tools, including human approval gates, scoped permissions, auditability, and security controls.
 * Experience deploying AI solutions in regulated, high-availability, industrial, or mission-critical environments.

## Description

We are seeking a Principal AI Platform Engineer to design and deliver enterprise-scale AI and cloud platform solutions. This is a highly hands-on technical leadership role combining Applied AI, Generative AI, cloud-native engineering, distributed systems, Azure/AWS, and industrial software.

You will work closely with Product, R&D, Architecture, Cloud Operations, and customer-facing teams to build secure, scalable, reusable, and production-ready solutions., * Design and build AI-enabled services, APIs, connectors, libraries, automation, and reusable platform components.

 * Develop production AI solutions using LLMs, Generative AI, RAG, AI agents, orchestration, vector search, grounding, evaluation, safety, monitoring, and cost optimization.
 * Architect cloud-native solutions using C#, .NET, ASP.NET Core, REST APIs, microservices, containers, Kubernetes, serverless, and event-driven architectures.
 * Engineer enterprise platforms across Microsoft Azure and AWS, including identity, data, messaging, API management, observability, Infrastructure as Code, and CI/CD.
 * Design and execute cloud migrations and Azure-to-AWS migration strategies, including networking, data movement, portability, resilience, cutover, and rollback.
 * Troubleshoot complex production issues involving performance, scalability, reliability, latency, security, and compliance.
 * Build solutions involving industrial/OT data, time-series data, historians, SCADA, MES, ERP/EAM, digital twins, and edge-to-cloud integration.
 * Use AI-assisted engineering for code modernization, refactoring, migration, performance analysis, testing, and developer productivity.
 * Provide technical leadership, influence architecture decisions, mentor engineers, and establish strong engineering practices.