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Fpga Embedded System Engineer Jobs in Maine (NOW HIRING)

NinjaOne

This means working close to the metal with system-level APIs, building resilient install and ... SQLite / Embedded database patterns * CMake * Proficiency working with Qt and Vcpkg a strong plus ...

Verdantas

Senior Professional Surveyor

Saco, ME

$45/hr

... engineers, geologists, and technical specialists, embedded in a people-focused culture ... Lidar Systems, and GPS. A successful candidate in this position takes pride in ensuring they ...

Olympus Corporation of the Americas

Partner with architects and engineering teams to validate solution designs, then support testing ... Strong understanding of hybrid infrastructure, including how cloud and on prem systems integrate ...

University of Rochester

$61K - $85K/yr

Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect ... and system and application analysts. Collaborates with technical team leads and/or resource ...

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Fpga Embedded System Engineer information

What is an FPGA Embedded System Engineer?

FPGA Embedded System Engineers are professionals who design, develop, and implement embedded systems using Field Programmable Gate Arrays (FPGAs). They create custom hardware solutions by programming FPGAs to perform specific tasks, often working closely with software and hardware teams. Their work involves hardware description languages like VHDL or Verilog, debugging, testing, and optimizing systems for performance, power, and efficiency. These engineers are crucial in industries like telecommunications, automotive, aerospace, and consumer electronics, where high-performance and flexible hardware solutions are needed.

How does an FPGA Embedded System Engineer typically collaborate with software and hardware teams during a project?

FPGA Embedded System Engineers often serve as a bridge between hardware and software teams, collaborating closely to ensure seamless integration of programmable logic with embedded software. They work with hardware engineers to define system requirements and interface specifications, while coordinating with software developers to implement and test embedded code on the FPGA platform. Regular meetings, design reviews, and the use of version control systems help facilitate smooth communication and resolve integration challenges. This collaborative approach ensures that both hardware and software components function together effectively, leading to successful project outcomes.

What are the key skills and qualifications needed to thrive as an FPGA Embedded System Engineer, and why are they important?

To thrive as an FPGA Embedded System Engineer, you need a strong background in digital design, hardware description languages (such as VHDL or Verilog), and embedded systems, typically supported by a degree in electrical engineering or a related field. Proficiency in using FPGA development tools like Xilinx Vivado or Intel Quartus, as well as experience with simulation and debugging tools, is crucial. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills help engineers excel in this role. These competencies ensure the successful design, implementation, and integration of reliable, high-performance embedded solutions.

What is the difference between Fpga Embedded System Engineer vs Digital Signal Processing (DSP) Engineer?

AspectFpga Embedded System EngineerDigital Signal Processing (DSP) Engineer
Required CredentialsBachelor's/Master's in Electrical Engineering, Computer Engineering; FPGA certificationsBachelor's/Master's in Electrical Engineering, Signal Processing, or related; DSP certifications
Work EnvironmentDesigning FPGA hardware, embedded software development, hardware testingDeveloping algorithms for signal processing, software implementation, testing
Industry UsageAerospace, defense, telecommunications, embedded systems

While both roles involve hardware and software skills, Fpga Embedded System Engineers focus on FPGA hardware design and embedded systems integration, whereas DSP Engineers specialize in developing algorithms for signal processing. Both roles often collaborate but serve different technical needs within similar industries.

What are popular job titles related to Fpga Embedded System Engineer jobs in Maine?

For Fpga Embedded System Engineer jobs in Maine, the most frequently searched job titles are:

What job categories do people searching Fpga Embedded System Engineer jobs in Maine look for?

The top searched job categories for Fpga Embedded System Engineer jobs in Maine are:

Fpga Embedded System Engineer jobs near you
Infographic showing various Fpga Embedded System Engineer job openings in Maine as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 3% Temporary, and 2% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Senior Full-Stack Engineer (Node.js & Next.js, AI-Native) - Remote

Lumimeds

Mexico, ME • Remote

Full-time

Re-posted 20 days ago

Job description

Platform & Product Engineering - LumiMeds
Location: Remote / Hybrid
Seniority: Mid-Level / Senior (Individual Contributor)
Role Overview

LumiMeds is a high-growth telehealth platform building the next generation of virtual telehealth infrastructure. We are looking for an AI-First Full-Stack Engineer who treats AI not as a tool but as a core part of how they think, build, and ship.

This is not a role for someone who occasionally uses Copilot to autocomplete lines. You are an engineer who has rebuilt how you work around AI- using LLMs to generate scaffolding, reason through architecture, write tests, debug production issues, and ship faster than a team twice the size. Critically, you know how to orchestrate Claude agent teams to parallelize complex engineering work, treating a coordinated group of Claude agents as a force multiplier on top of your own output. You will balance 90% hands-on coding with 10% knowledge sharing, and you are expected to push the velocity ceiling of what one engineer can deliver.

Core Technical Domains

You will build and scale the following critical healthcare systems:

  • EMR & Clinical Data Engine: Implementing high-availability Electronic Medical Record (EMR) systems with complex data modeling for patient history and clinical notes.
  • AI Clinical Copilot: Integrating LLMs to automate clinical documentation, summarize patient charts, and surface actionable insights for providers.
  • Prescription Management (e-Prescribing): Building secure, auditable workflows for medication orders, pharmacy integrations, and state-machine-based fulfillment tracking.
  • Virtual Care Infrastructure: Implementing real-time patient-provider interfaces, including WebRTC video, secure messaging, and async consultation flows.
  • E-commerce & Checkout: Engineering high-conversion storefront experiences, including complex product catalogs, subscription billing models, and dynamic pricing engines.
Key Responsibilities
  • AI-Augmented Development: Use Cursor, Copilot, and LLM APIs as first-class engineering tools - not as an afterthought. Generate, validate, and iterate on code at machine speed.
  • Claude Agent Team Orchestration: Design and operate teams of Claude agents to parallelize engineering work - breaking large tasks into agent-
  • executable subtasks, managing context handoffs between agents, and coordinating outputs into coherent, production-ready deliverables. This is a core competency, not a bonus.
  • Full-Stack Feature Ownership: Drive end-to-end delivery across Node.js backends and Next.js frontends, from schema design to production deployment.
  • LLM Product Integration: Build and iterate on AI-powered product features - prompt pipelines, RAG architectures, structured output parsing, and agentic workflows embedded into clinical and consumer interfaces.
  • Production Quality: Maintain high standards for API contracts, database schema migrations, CI/CD pipelines, and observability. AI-generated code is your code - you own its correctness.
  • Compliance & Security: Ensure all systems meet HIPAA/SOC2 standards, focusing on data encryption, audit logs, and PII protection.
Required Hard Skills & Tech Stack

Backend & API:

  • Node.js & TypeScript: Strong command of async patterns, event-driven architecture, and runtime performance.
  • API Design: Proficiency in RESTful, GraphQL, and TypeSafe APIs (tRPC).
  • Database: Solid PostgreSQL fundamentals (joins, indexing, migrations) and Redis for caching.

Frontend:

  • Next.js & React: Working knowledge of App Router, Server Components (RSC), and client/server data flow.
  • State Management: Experience with TanStack Query, Zustand, or similar.

AI & Infrastructure:

  • LLM Integration: Hands-on experience integrating OpenAI or Anthropic APIs into production environments - streaming, tool use, structured outputs.
  • Claude Agent Teams: Demonstrated experience building and orchestrating Claude agent teams using the Claude Agent SDK. You know how to decompose a problem, spin up specialized subagents, manage inter-agent communication, and stitch outputs back into a reliable, production-ready result.
  • AI Dev Tooling: Daily active use of Cursor, GitHub Copilot, or equivalent. You have strong opinions about how to prompt effectively.
  • Cloud & DevOps: Familiarity with AWS (EC2, RDS, Lambda, S3), Vercel, and GitHub Actions.
Candidate Qualifications
  • 3+ years of professional software engineering experience.
  • AI-Native Workflow: You can demonstrate, concretely, how AI has changed the way you write and ship software. Portfolio or examples preferred.
  • Full-Stack Range: Comfortable moving between backend logic and frontend implementation without hand-holding.
  • High Agency: Ability to operate in ambiguous environments, self-direct, and make high-leverage decisions without constant supervision.
  • Communication: Professional proficiency in English for technical documentation and async collaboration.
Why Join LumiMeds?
  • AI as Infrastructure: We don't treat AI as a feature - it's woven into how we build, test, document, and ship. You'll be in the right environment to go further than anywhere else.
  • High Complexity: Work on hard engineering problems involving real-time data, complex clinical state machines, and high-stakes reliability.
  • Direct Impact: Your code will directly affect patient outcomes and the efficiency of healthcare providers.

Apply