2

Remote Ai Implementation Jobs in Maine (NOW HIRING)

Software Engineer

Portland, ME ยท On-site +1

$90K - $100K/yr

Remote Compensation: $90,000 - $100,000 / year Description Why Work Here? At Arkatechture, we have ... Whether it's modernizing infrastructure, building analytics platforms, or leveraging AI for smarter ...

... AI to deliver solutions. Responsible for implementing design patterns and working on enterprise ... Location We are flexible on remote working from home, if you are located in the USA and reside in ...

A flexible remote work policy with optional access to our Portland, Maine office * A 4-day workweek ... Perform root cause analysis and implement long-term solutions to prevent recurring issues. * Build ...

Senior Operational Engineer

Portland, ME ยท Remote

$106K - $146K/yr

Experience working within Agile delivery frameworks and collaborating with distributed or remote ... Experience designing, implementing, or supporting AI-enabled solutions within cloud environments.

Senior Operational Engineer

Portland, ME ยท Remote

$106K - $146K/yr

Experience working within Agile delivery frameworks and collaborating with distributed or remote ... Experience designing, implementing, or supporting AI-enabled solutions within cloud environments.

You are responsible for implementing design patterns and working on enterprise level software ... Comfortable experimenting with AI tools in development workflow. Preferred Experience: * Experience ...

About the Role NinjaOne's Vulnerability Management team is building the real-time, AI-driven engine ... Location - We are flexible on remote working from home, if you are located in the USA and reside in ...

Location -- We are flexible on remote working from home, if you are located in the USA and reside ... Leverage AI-assisted development tools and techniques to improve engineering productivity and ...

next page

Showing results 1-20

Remote Ai Implementation information

What is a remote AI implementation specialist?

A Remote AI Implementation Specialist is a professional who helps organizations deploy and integrate artificial intelligence (AI) solutions without being physically present on-site. They work remotely to assess business needs, customize AI models, oversee technical setups, and ensure seamless integration with existing systems. These specialists often collaborate with cross-functional teams, provide training, and troubleshoot issues to ensure AI tools deliver maximum value. Their expertise enables companies to adopt advanced AI technologies efficiently, regardless of geographic location.

What are the key skills and qualifications needed to thrive as a remote AI implementation specialist?

To thrive as a Remote AI Implementation Specialist, you need a strong background in computer science, data analysis, and AI/machine learning concepts, often supported by a relevant degree or certification. Proficiency with programming languages (such as Python or R), cloud platforms (like AWS or Azure), and AI frameworks (such as TensorFlow or PyTorch) is essential. Exceptional problem-solving, communication, and project management skills help you collaborate effectively and translate business needs into technical solutions. These skills ensure successful deployment of AI solutions that align with organizational goals while facilitating smooth remote teamwork and client interactions.

What are some common challenges faced when implementing AI solutions remotely, and how can they be addressed?

One common challenge in remote AI implementation is maintaining clear communication and alignment between distributed teams, especially when dealing with complex data and evolving project requirements. To address this, regular virtual meetings, detailed documentation, and collaborative project management tools are essential. Additionally, ensuring secure and efficient access to data and resources can be tricky, so robust cybersecurity protocols and cloud-based platforms are often used. Open feedback channels and cross-functional collaboration also help in quickly resolving technical issues and adapting solutions to client needs.

What is the difference between Remote Ai Implementation vs Data Scientist?

AspectRemote Ai ImplementationData Scientist
Required CredentialsAI certifications, programming skills, knowledge of ML frameworksStatistics, programming, data analysis, often a degree in related field
Work EnvironmentCollaborative teams, project-based, often client-facingResearch-focused, data analysis, model development
Industry UsageTech, finance, healthcare, retailTech, finance, healthcare, academia
Search & Comparison IntentImplementing AI solutions remotelyAnalyzing data, building models

Remote Ai Implementation involves deploying AI solutions across various industries, focusing on technical deployment and integration. Data Scientists analyze data and develop models, often in research or analytical roles. While both roles require programming and AI knowledge, Remote Ai Implementation emphasizes deployment skills, whereas Data Scientists focus on data analysis and model creation.

What are popular job titles related to Remote Ai Implementation jobs in Maine?

For Remote Ai Implementation jobs in Maine, the most frequently searched job titles are:

What cities in Maine are hiring for Remote Ai Implementation jobs?

Cities in Maine with the most Remote Ai Implementation job openings:

Infographic showing various Remote Ai Implementation job openings in Maine as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

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

Lumimeds

Mexico, ME โ€ข Remote

Full-time

Re-posted 2 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-Stackย 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- usingย 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.