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Kernel Engineer Jobs in Florida (NOW HIRING)

Embedded Software Engineer

Tampa, FL · On-site

$174K - $261K/yr

What you'll do This is a role for a Embedded Software Engineer who is eager to contribute to a ... Linux kernel driver development/modifications * Familiarity with to bare metal embedded device ...

As a Senior Software Engineer at Iru, you'll help design, build, and evolve our proprietary Windows ... Kernel Driver Development : Experience writing or debugging kernel-mode drivers, filter drivers, or ...

As a Senior Software Engineer at Iru, you'll help design, build, and evolve our proprietary Windows ... Kernel Driver Development : Experience writing or debugging kernel-mode drivers, filter drivers, or ...

$117K - $154K/yr

As a Senior Software Engineer at Iru, you'll help design, build, and evolve our proprietary Windows ... Kernel Driver Development : Experience writing or debugging kernel-mode drivers, filter drivers, or ...

... the kernel and application levels, for both the Intel/AMD and ARM64 architectures. The real-time software engineer is responsible for executing or independently achieving project objectives by ...

... Kernel), and building modern AI agent and orchestration patterns • Proven experience designing ... DevOps, Git for version control, and implementing CI/CD pipelines for automated testing and ...

Embedded Software Engineer

Tampa, FL · On-site

$124K - $163K/yr

The engineer will work closely with electrical, mechanical, software, and production teams to ... Experience with Linux kernel development or embedded Linux environments. * Familiarity with ROS2.

Showing results 41-60

Kernel Engineer information

What is a kernel engineer?

A Kernel Engineer is a software engineer who specializes in the development, maintenance, and optimization of operating system kernels, such as Linux or Windows. Their primary responsibilities include designing new kernel features, fixing bugs, improving performance, and ensuring compatibility with hardware. They often work closely with hardware manufacturers and other software developers to build stable and secure system foundations. Kernel Engineers must have a deep understanding of operating system internals, low-level programming (typically in C or C++), and computer architecture. This role is critical for maintaining and advancing the core components that allow computers and devices to function efficiently.

What are the key skills and qualifications needed to thrive as a kernel engineer, and why are they important?

To thrive as a Kernel Engineer, you need deep expertise in C programming, operating system concepts, and low-level hardware interactions, typically supported by a degree in computer science or related fields. Familiarity with version control systems (like Git), debugging tools (such as GDB), and kernel development frameworks is crucial. Problem-solving, attention to detail, and effective communication are standout soft skills in this role. These skills enable the creation of reliable, efficient, and secure kernels that form the backbone of computing systems.

What are some typical challenges kernel engineers face when working on operating system updates?

Kernel Engineers often encounter challenges related to maintaining system stability and compatibility when implementing updates or new features. Ensuring that changes do not introduce regressions or security vulnerabilities requires thorough testing and collaboration with QA and other engineering teams. Additionally, Kernel Engineers need to keep up-to-date with hardware advancements and support a wide range of devices, which can add complexity to their work. Effective communication and strong problem-solving skills are essential for navigating these challenges and delivering high-quality code.

What is the difference between Kernel Engineer vs Device Driver Developer?

AspectKernel EngineerDevice Driver Developer
Required CredentialsBachelor's or higher in Computer Science, Linux/Unix knowledge, programming skills in C/C++Similar credentials, often with specialized knowledge in hardware and driver development
Work EnvironmentSystem-level development, kernel code, Linux/Unix environmentsHardware interaction, driver coding, embedded or OS-specific environments
Industry UsageOperating system development, open-source projects, hardware manufacturersHardware companies, embedded systems, OS vendors
Common Search/ComparisonKernel EngineerDevice Driver Developer

Kernel Engineers focus on developing and maintaining the core kernel of operating systems, ensuring system stability and performance. Device Driver Developers specialize in creating software that allows hardware components to communicate with the OS. While both roles require similar technical skills and often overlap, Kernel Engineers work on the entire kernel infrastructure, whereas Device Driver Developers concentrate on specific hardware interfaces.

What job categories do people searching Kernel Engineer jobs in Florida look for?

The top searched job categories for Kernel Engineer jobs in Florida are:

Infographic showing various Kernel Engineer job openings in Florida as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 84% In-person, and 16% Remote job distribution.

Information Technology_USA - USA_Developer

Real Soft, Inc.

Jacksonville, FL • On-site

Contractor

Re-posted 5 days ago


Job description

Job Description: **Please strictly adhere to the following resume naming convention:ALL CAPS, NO SPACES B/T UNDERSCORESPTN_US_GBAMSREQID_CandidateBeelineIDi.e. PTN_US_9999999_SKIPJOHNSON0413: -/hrMSP Owner: Subhashree SamalLocation: New York, NY- onsiteDuration: 6 monthsGBaMS ReqID: 10923817 Job Title : Sr Backend Engineer with AI (Backend Architect)Experience Req : 12-14 Years"12+ years of experience in designing and building enterprise-scale, cloud-native backend systems and distributed architectures. • Strong hands-on expertise in Node.js, JavaScript, and TypeScript (must-have), with working knowledge of Python and Go. • Extensive experience developing microservices, REST/gRPC APIs, event-driven architectures, and scalable backend platforms. • Strong expertise in AWS and/or GCP, Kubernetes, Docker, cloud-native architecture, and CI/CD pipelines. • Experience with distributed messaging and streaming technologies such as Kafka, queues, and asynchronous processing. • Proven experience designing highly available, secure, scalable, and resilient backend systems. • Strong understanding of databases (SQL/NoSQL), caching, observability, logging, and performance optimization. • Mandatory experience integrating Large Language Models (LLMs) into enterprise applications and backend platforms. • Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or Semantic Kernel. • Experience building Retrieval-Augmented Generation (RAG) pipelines, AI orchestration workflows, and LLM gateways. • Working knowledge of PyTorch, Hugging Face ecosystem, embeddings, inference, and model evaluation. • Strong understanding of AI governance, evaluation, safety, and responsible AI practices.• Excellent architecture, technical leadership, stakeholder management, and mentoring skills. • Required Technologies o Languages: Node.js, JavaScript, TypeScript, Python, Go o Cloud: AWS/GCP o Containers: Kubernetes, Docker o APIs: REST, gRPC o Messaging: Kafka or equivalent o AI Frameworks: LangGraph, LangChain, LlamaIndex, CrewAI, Semantic Kernel o ML: Hugging Face, PyTorch o DevOps: CI/CD, Terraform (preferred)"Lead the architecture, design, and implementation of scalable cloud-native backend platforms for Lounge Services. • Design and develop high-performance microservices and APIs using Node.js/TypeScript on AWS/GCP. • Define architecture standards for distributed systems, event-driven solutions, messaging, and cloud-native applications. • Drive the adoption of AI capabilities by integrating LLMs and Agentic AI into enterprise backend services. • Design and implement reusable AI platform components including orchestration, RAG pipelines, model gateways, and AI observability. • Provide technical leadership across engineering teams, driving architecture reviews, engineering best practices, and technology decisions. • Collaborate with Product, Engineering, Security, and Enterprise Architecture teams to deliver scalable and secure solutions. • Mentor engineering teams and influence technical direction across multiple initiatives. • Evaluate emerging backend, cloud, and AI technologies and recommend enterprise adoption where appropriate. • Ensure solutions meet enterprise standards for scalability, reliability, security, performance, and operational excellence.Node.js, Cloud & AIRole Descriptions: Technical/Functional Skills 12+ years of experience in designing and building enterprise-scale| cloud-native backend systems and distributed architectures.Strong hands-on expertise in Node.js| JavaScript| and TypeScript (must-have)| with working knowledge of Python and Go.Extensive experience developing microservices| REST/gRPC APIs| event-driven architectures| and scalable backend platforms.Strong expertise in AWS and/or GCP| Kubernetes| Docker| cloud-native architecture| and CI/CD pipelines.Experience with distributed messaging and streaming technologies such as Kafka| queues| and asynchronous processing.Proven experience designing highly available| secure| scalable| and resilient backend systems.Strong understanding of databases (SQL/NoSQL)| caching| observability| logging| and performance optimization.Mandatory experience integrating Large Language Models (LLMs) into enterprise applications and backend platforms.Hands-on experience with Agentic AI frameworks such as LangGraph| LangChain| LlamaIndex| CrewAI| or Semantic Kernel.Experience building Retrieval-Augmented Generation (RAG) pipelines| AI orchestration workflows| and LLM gateways.Working knowledge of PyTorch| Hugging Face ecosystem| embeddings| inference| and model evaluation.Strong understanding of AI governance| evaluation| safety| and responsible AI practices.Excellent architecture| technical leadership| stakeholder management| and mentoring skills.Required TechnologiesoLanguages: Node.js| JavaScript| TypeScript| Python| GooCloud: AWS/GCPoContainers: Kubernetes| DockeroAPIs: REST| gRPCoMessaging: Kafka or equivalentoAI Frameworks: LangGraph| LangChain| LlamaIndex| CrewAI| Semantic KerneloML: Hugging Face| PyTorchoDevOps: CI/CD| Terraform (preferred)Roles & ResponsibilitiesLead the architecture| design| and implementation of scalable cloud-native backend platforms for Lounge Services.Design and develop high-performance microservices and APIs using Node.js/TypeScript on AWS/GCP.Define architecture standards for distributed systems| event-driven solutions| messaging| and cloud-native applications.Drive the adoption of AI capabilities by integrating LLMs and Agentic AI into enterprise backend services.Design and implement reusable AI platform components including orchestration| RAG pipelines| model gateways| and AI observability.Provide technical leadership across engineering teams| driving architecture reviews| engineering best practices| and technology decisions.Collaborate with Product| Engineering| Security| and Enterprise Architecture teams to deliver scalable and secure solutions.Mentor engineering teams and influence technical direction across multiple initiatives.Evaluate emerging backend| cloud| and AI technologies and recommend enterprise adoption where appropriate.Ensure solutions meet enterprise standards for scalability| reliability| security| performance| and operational excellence.Essential Skills: Technical/Functional Skills 12+ years of experience in designing and building enterprise-scale| cloud-native backend systems and distributed architectures.Strong hands-on expertise in Node.js| JavaScript| and TypeScript (must-have)| with working knowledge of Python and Go.Extensive experience developing microservices| REST/gRPC APIs| event-driven architectures| and scalable backend platforms.Strong expertise in AWS and/or GCP| Kubernetes| Docker| cloud-native architecture| and CI/CD pipelines.Experience with distributed messaging and streaming technologies such as Kafka| queues| and asynchronous processing.Proven experience designing highly available| secure| scalable| and resilient backend systems.Strong understanding of databases (SQL/NoSQL)| caching| observability| logging| and performance optimization.Mandatory experience integrating Large Language Models (LLMs) into enterprise applications and backend platforms.Hands-on experience with Agentic AI frameworks such as LangGraph| LangChain| LlamaIndex| CrewAI| or Semantic Kernel.Experie