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Remote Embedded Ai Jobs (NOW HIRING)

Senior Front-End Agentic AI Engineer

OR ยท On-site +1

$122K - $168K/yr

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Build and maintain conversational interfaces, embedded AI assistants, review workflows, and ...

Senior Front-End Agentic AI Engineer

$125K - $172K/yr

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Build and maintain conversational interfaces, embedded AI assistants, review workflows, and ...

Senior AI Enablement Engineer

$125K - $165K/yr

Location: Georgia, Remote * Language: Fluent in English and Russian About Fundraise Up We're ... Scale through champions - stand up and support a network of embedded AI champions so enablement ...

Senior Product Manager - Growth & Engagement

OR ยท On-site +1

$126K - $166K/yr

This role is open to remote, but preferably based in NYC where you'll work from our office Monday ... Design and ship embedded AI features as core parts of the product experience - like AI-powered ...

Sr. Embedded Software Engineer

$126K - $166K/yr

Remote Compensation : $100,000 - $130,000 + Bonus Eligible Who we are: Lynx delivers modular, open ... AI : LYNX MOSA.ic.AI is a unified CPU and GPU software platform that enables deterministic ...

Embraces AI as part of a modern engineering toolkit. * Excellent communication skills, fluency in ... Fully remote role and requires 20% travel, including domestic and international. Benefits Our ...

Embedded AI-driven insights and task execution * Real-time iteration inside an operating agency ... Limited remote flexibility is possible, but proximity to the agency is critical to success. Miami ...

Showing results 21-40

Remote Embedded Ai information

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$70K

$153.4K

$174K

How much do remote embedded ai jobs pay per year?

As of Sep 13, 2026, the average yearly pay for remote embedded ai in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is a remote embedded AI engineer?

A Remote Embedded AI engineer is a professional who develops and integrates artificial intelligence (AI) algorithms into embedded systems, such as IoT devices, sensors, or smart appliances, while working from a remote location. Their role involves optimizing AI models to run efficiently on hardware with limited resources, ensuring reliable performance and low power consumption. These engineers typically collaborate with cross-functional teams to deliver intelligent, connected products, leveraging skills in machine learning, software development, and embedded hardware. Working remotely allows them to contribute to global projects without being tied to a specific office location.

What are the key skills and qualifications needed to thrive as a remote embedded AI engineer?

To thrive as a Remote Embedded AI Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++, Python, or TensorFlow Lite, often supported by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), edge AI development platforms, and version control tools such as Git is typically required. Strong problem-solving skills, effective remote communication, and self-motivation help you excel in collaborative yet independent work environments. These competencies are crucial for building efficient, innovative AI solutions on hardware platforms while ensuring seamless teamwork across distributed teams.

What are some common challenges faced by remote embedded AI engineers, and how can they be overcome?

Remote Embedded AI Engineers often encounter challenges such as limited access to hardware for testing, asynchronous communication with distributed teams, and integrating AI models within resource-constrained embedded systems. Overcoming these challenges involves utilizing remote debugging tools, setting up robust simulation environments, and maintaining clear, regular communication with team members. Collaboration platforms and thorough documentation help ensure smooth coordination, while staying updated on best practices in embedded AI can address technical limitations.

What is the difference between Remote Embedded Ai vs Remote Machine Learning Engineer?

AspectRemote Embedded AiRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; experience with embedded systemsBachelor's or higher in Computer Science, Data Science, or related fields; strong programming and statistical skills
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsCloud platforms, data centers, software development environments
Industry UsageConsumer electronics, automotive, industrial IoTTech companies, finance, healthcare, research
Common Search/ComparisonYesNo

Remote Embedded Ai professionals focus on developing AI algorithms for embedded hardware and real-time systems, often working with IoT devices and specialized hardware. In contrast, Remote Machine Learning Engineers primarily develop models in cloud environments for data analysis and prediction. While both roles require strong programming skills, Embedded Ai emphasizes hardware integration, whereas Machine Learning Engineers focus on scalable model deployment.

More about Remote Embedded Ai jobs

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What are the most commonly searched types of Embedded Ai jobs?

The most popular types of Embedded Ai jobs are:

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Infographic showing various Remote Embedded Ai job openings in the United States as of September 2026, with employment types broken down into 89% Full Time, 2% Part Time, 2% Temporary, and 7% Contract. Highlights an 100% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Senior Front-End Agentic AI Engineer

OR โ€ข On-site, Remote

$122K - $168K/yr

Full-time

Re-posted 14 days ago


Job description

United States - Remote
Clearance: Ability to obtain and maintain a Public Trust

LTS is seeking a Senior Front-End Agentic AI Engineer to own the experience layer of an AI platform built for one of the most consequential legacy systems still running in production today.

Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to the exact lines of source code. Rather than replacing engineers, we're building AI that helps them understand decades of complex software faster, with complete transparency and confidence.

We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. Every response generated by the platform must be explainable, traceable, and trustworthy. The front end is where that trust is earned.

The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.

When an engineer asks a question about a decades-old codebase, your interface determines whether they trust the answer or close the tab. You'll own that experience from end to end.

The product has executive sponsorship, committed users, a clearly defined mission, and a customer who knows exactly what success looks like.

Our engineering team is intentionally small. Every engineer has significant ownership, meaningful influence over product direction, and the opportunity to help define how engineers interact with AI.

We don't simply build AI-powered software-we build software with AI. This is not another chatbot.

Using AI agents, LLMs, parallel workflows, and model-assisted development is simply how we engineer.

What You'll Do:

  • Own the end-to-end front-end experience for an enterprise-scale Agentic AI platform.
  • Design intuitive interfaces that transform complex AI reasoning into experiences engineers' trust.
  • Build and maintain conversational interfaces, embedded AI assistants, review workflows, and authoring experiences using React, TypeScript, and modern front-end technologies.
  • Develop the rendering pipeline for streaming AI responses, markdown, source citations, code blocks, dependency graphs, workflow visualizations, and technical documentation.
  • Build evidence and traceability experiences that allow users to validate AI-generated answers by navigating directly to source code, documentation, and supporting artifacts.
  • Design interaction patterns for agentic workflows, including multi-step reasoning, tool execution, progress visualization, human-in-the-loop review, and long-running AI tasks.
  • Build responsive real-time user experiences using WebSockets, streaming APIs, and modern state management patterns.
  • Partner closely with AI engineers to define how agent output is translated into intuitive user experiences.
  • Collaborate with product managers, UX designers, architects, and platform engineers to rapidly prototype, validate, and deliver new capabilities.
  • Build scalable component libraries and reusable design systems supporting future platform growth.
  • Optimize performance, accessibility, responsiveness, and usability across enterprise environments, including Section 508 compliance.
  • Instrument the application with analytics, observability, and client-side monitoring to continuously improve user experience.
  • Use AI-native engineering workflows to accelerate development, improve software quality, and increase engineering velocity.

What We're Looking For:

  • Bachelor's degree in Computer Science, Software Engineering, or related discipline (or equivalent professional experience).
  • 7+ years of professional front-end software engineering experience building production web applications.
  • Expert-level proficiency with React, TypeScript, modern JavaScript, and contemporary front-end architecture.
  • Experience building highly interactive, data-rich user interfaces.
  • Strong understanding of component architecture, state management, and scalable front-end engineering.
  • Experience building real-time user experiences using streaming APIs, WebSockets, or Server-Sent Events.
  • Experience consuming complex REST, GraphQL, tRPC, or comparable typed APIs.
  • Experience collaborating closely with backend engineers, designers, and product teams in Agile environments.
  • Excellent communication skills and the ability to explain technical decisions clearly across engineering and business stakeholders.
  • Mindset of a product engineer rather than a feature developer.
  • Engineers capable of building software from first principles.
  • Passion for usability, interaction design, and developer experience.
  • Strong ability to carefully analyze requirements before writing code.
  • Preference for ownership over narrowly defined responsibilities.
  • Experience operating across the client/server boundary when necessary.
  • Expertise using AI coding assistants, parallel agents, and model-driven development workflows.
  • Efficiency while maintaining high engineering standards.
  • Innate ability to solve difficult engineering problems that don't have obvious solutions.

Nice to Have:

  • Experience in healthcare, regulated industries, or large-scale enterprise modernization programs is a plus.
  • Experience building AI-native products, LLM-powered applications, or agentic AI systems.
  • Experience designing interfaces for AI assistants, copilots, developer tools, or knowledge platforms.
  • Familiarity with Retrieval-Augmented Generation (RAG), vector search, embeddings, or agent orchestration frameworks.
  • Experience rendering complex technical content including markdown, syntax highlighting, dependency graphs, diagrams, or code relationships.
  • Experience developing products for software engineers or other highly technical users.
  • Experience with cloud-native platforms including AWS or Azure.
  • Experience building design systems or reusable component libraries.
  • Familiarity with accessibility standards including Section 508 and WCAG.
  • Experience using AI coding assistants and parallel AI workflows as part of daily software development.

Why Join LTS?

At LTS, we support impactful programs that directly improve healthcare services for Veterans nationwide. Our teams work on innovative modernization initiatives that help transform legacy systems into secure, scalable, and mission-focused digital solutions. We value collaboration, integrity, and professional growth while empowering employees to contribute to meaningful federal healthcare missions.