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Remote Computer Science Artificial Intelligence Jobs in Maine

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Remote Computer Science Artificial Intelligence information

What is the difference between Remote Computer Science Artificial Intelligence vs Remote Data Science?

AspectRemote Computer Science Artificial IntelligenceRemote Data Science
Required CredentialsBachelor's or higher in Computer Science, AI certificationsBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentSoftware development, AI model training, algorithm designData analysis, visualization, statistical modeling
Employer & Industry UsageTech companies, research labs, AI startupsFinance, healthcare, e-commerce, tech firms
Common Search & ComparisonYesNo

Remote Computer Science Artificial Intelligence roles focus on developing AI algorithms, machine learning models, and software solutions. In contrast, Remote Data Science involves analyzing data, creating visualizations, and deriving insights. While both fields require strong technical skills and often similar educational backgrounds, their core responsibilities differ, making each suitable for different career interests within the tech industry.

What are the key skills and qualifications needed to thrive as a Remote Computer Science Artificial Intelligence professional, and why are they important?

To thrive as a Remote Computer Science Artificial Intelligence professional, you need a strong background in computer science fundamentals, mathematics, machine learning, and programming languages such as Python, often supported by a relevant degree. Familiarity with AI frameworks (like TensorFlow or PyTorch), cloud platforms, and version control systems is typically required, along with certifications in AI or data science. Excellent problem-solving, self-motivation, and effective remote communication skills help you stand out in distributed teams. These skills and qualities are crucial for developing robust AI solutions, collaborating virtually, and adapting to fast-evolving technologies.

What are Remote Computer Science Artificial Intelligence jobs?

Remote Computer Science Artificial Intelligence (AI) jobs involve working from a location outside of a traditional office to design, develop, and implement AI systems and algorithms. Professionals in this field use programming, data analysis, and machine learning techniques to solve complex problems in areas such as natural language processing, computer vision, and robotics. These roles often require strong knowledge of mathematics, statistics, and programming languages like Python or Java. Remote AI jobs offer flexibility and the opportunity to collaborate with global teams using digital communication tools.

How do remote Computer Science Artificial Intelligence professionals typically collaborate with team members across different time zones?

Remote AI professionals often work with global teams, requiring strong communication and collaboration skills. Teams frequently use project management tools, shared code repositories, and regular video meetings to stay aligned on goals and progress. Flexibility with meeting times and thorough documentation are essential for ensuring smooth collaboration. Building rapport through virtual channels and actively participating in discussions helps foster a sense of teamwork despite physical distance.
What are popular job titles related to Remote Computer Science Artificial Intelligence jobs in Maine? For Remote Computer Science Artificial Intelligence jobs in Maine, the most frequently searched job titles are:
What job categories do people searching Remote Computer Science Artificial Intelligence jobs in Maine look for? The top searched job categories for Remote Computer Science Artificial Intelligence jobs in Maine are:
What cities in Maine are hiring for Remote Computer Science Artificial Intelligence jobs? Cities in Maine with the most Remote Computer Science Artificial Intelligence job openings:

Staff Software Engineer | Semantic Data Lake

eNett

Portland, ME • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago


Job description

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; San Francisco Bay Area, CA; and Seattle/WA.

About the Team/Role

WEX is reimagining its enterprise data platform with a powerful goal: transforming raw data into semantically meaningful, reusable, and trusted business assets. As a Staff Software Engineer on the Semantic Data Lake Team, you'll play a critical role in designing, building, and maintaining our core 360 data objects-such as Customer360, Fleet360, and Provider360.

These wide, entity-based tables are foundational to our analytics, AI, and product platforms. You'll implement rich transformation logic, encode business rules, and ensure data consistency across domains, making our data models both technically scalable and business-ready.

This team is at the heart of WEX's DaaS platform-bridging raw data with meaningful business insights. You'll help define and deliver the semantic backbone of our products, analytics, and machine learning systems.

We're looking for an AI-native engineer: someone who builds with modern AI coding tools (Claude, Copilot, Cursor, and similar) and Spec-Driven Development (SDD) as a core part of their daily workflow, not an occasional add-on. You'll use these tools to accelerate design, generate and refactor transformation logic, write tests, document semantics, and explore data-while applying the engineering judgment needed to ship production-grade, trustworthy data assets.

If you're excited about building semantic models that carry real-world meaning, scale to billions of records, and unify how a business understands its world-and doing it with the leverage of modern AI tooling-this is your next big move.

How you'll make an impact
  • Design and implement semantically consistent, scalable 360 data models that integrate data across domains.

  • Build and maintain transformation pipelines that apply cleansing, standardization, enrichment, and derived logic to domain datasets.

  • Write production-quality, testable code in SQL and Python (or equivalent)-delivering performant and maintainable data assets.

  • Leverage AI coding assistants (Claude, Copilot, Cursor, and similar) to accelerate development-drafting transformation logic, generating tests, refactoring pipelines, exploring datasets, and producing semantic documentation-while critically reviewing AI output for correctness, performance, and alignment with business rules.

  • Develop and share patterns, prompts, and workflows that help the team get more leverage out of AI tooling, raising the bar for AI-native engineering practices across the Semantic Data Team.

  • Work closely with domain experts, data scientists, and product stakeholders to translate business concepts into interpretable, decision-ready data models.

  • Implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage.

  • Help define and enforce standards for data modeling, documentation, and governance within the semantic layer-including standards for responsible, auditable use of AI-generated code and artifacts.

  • Collaborate across teams to integrate with ingestion, MDM, and data product layers, and explore opportunities to expose 360 objects to LLM-powered and agentic applications.

Experience you'll bring
  • 8+ years of experience in data engineering or software engineering with a focus on data transformation, modeling, or analytics platforms.

  • Strong proficiency in SQL and at least one general-purpose language such as Python or Scala.

  • Demonstrated experience as an AI-native engineer-using tools like Claude, GitHub Copilot, Cursor, or similar as part of your everyday development workflow, with a clear point of view on where they accelerate your work and where human judgment is essential.

  • Comfort with modern AI engineering practices such as prompt design, context engineering, Spec-Driven Development (SDD), AI-assisted code review, and integrating LLMs or AI agents into engineering or data workflows.

  • Experience building and scaling wide, entity-based tables and modeling domain concepts (e.g., customer, fleet, provider) into durable data objects.

  • Solid understanding of data quality practices-including validation, enrichment, schema enforcement, and business rule encoding.

  • Experience working with large-scale datasets and optimizing transformation pipelines for performance and maintainability.

  • Comfort operating in a collaborative, cross-functional environment, balancing business logic with platform scalability.

  • A mindset for traceability, reproducibility, and semantic clarity-you build data models others (humans and AI systems alike) can trust and reuse.

Bachelor's degree in Computer Science, Software Engineering, or related field. A Master's or PhD in Data Science, Machine Learning, Artificial Intelligence, Computer Science, or Statistics is a big plus.

    The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $140,600.00 - $173,100.00