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Remote Generative Ai Jobs in Alaska (NOW HIRING)

Sedgwick

Data Engineer AI

Minto, AK · On-site +1

$118K - $142K/yr

Develop the data pipelines required for Generative AI, including the automated extraction, chunking ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Stratford Davis

UI/UX Designer

Anchorage, AK · On-site +1

$12 - $15/hr

... generative AI applications to accelerate research, prototyping, asset generation, and workflow ... Flexible scheduling with remote/hybrid work options.

New

Symmetry

$15.25 - $20.50/hr

Proficiency with generative AI * Video editing skills * Experience with motion graphics or ... Remote Duration: 10-12 weeks (Summer 2025)

Symmetry

$15.50 - $20.50/hr

Proficiency with generative AI * Video editing skills * Experience with motion graphics or ... Remote Duration: 10-12 weeks (Summer 2025)

Symmetry

$16 - $21.25/hr

Proficiency with generative AI * Video editing skills * Experience with motion graphics or ... Remote Duration: 10-12 weeks (Summer 2025)

All JobsGenerative Ai JobsRemote Generative Ai JobsRemote Generative Ai Jobs in Alaska

Remote Generative Ai information

What are some common challenges faced by Remote Generative AI professionals and how can they be addressed?

Remote Generative AI professionals often face challenges such as collaborating effectively across time zones, ensuring data security, and staying updated with rapidly evolving AI technologies. To overcome these, it's important to establish clear communication channels, utilize version control and collaboration tools, and participate in regular team meetings. Additionally, investing time in continuous learning through online courses and AI research communities can help professionals stay current with industry advancements.

What are the key skills and qualifications needed to thrive as a Remote Generative AI Specialist, and why are they important?

To thrive as a Remote Generative AI Specialist, you need strong expertise in machine learning, deep learning, and programming languages like Python, often supported by a degree in computer science or a related field. Proficiency with frameworks such as TensorFlow or PyTorch, cloud platforms, and relevant certifications (e.g., Google Cloud ML Engineer) is highly beneficial. Effective problem-solving, self-motivation, and clear communication are crucial for collaborating remotely and driving innovative AI solutions. These skills ensure you can develop, deploy, and improve generative AI models efficiently in distributed work environments.

Is generative AI a good career?

A career in generative AI offers opportunities in developing and deploying AI models, requiring skills in machine learning, programming, and data analysis. The field is growing rapidly with high demand for expertise, making it a promising option for those interested in AI technology and innovation.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and programming. These positions usually involve leadership responsibilities, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact. Such roles are rare and generally found in large tech companies or specialized AI firms.

Which 3 jobs will survive AI?

For a Remote Generative AI role, jobs that require complex human judgment, creativity, and emotional intelligence are likely to persist, such as AI ethics specialists, creative content creators, and AI trainers or annotators. These roles involve nuanced decision-making, understanding context, and overseeing AI outputs, which are difficult to fully automate. Skills in critical thinking, domain expertise, and collaboration will remain valuable in AI-related fields.

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

AspectRemote Generative AiData Scientist
Required CredentialsKnowledge of AI/ML, programming skills, familiarity with NLP and deep learningStatistics, programming, data analysis, often a degree in CS, stats, or related fields
Work EnvironmentRemote, collaborative teams, AI research labs, tech companiesRemote or on-site, data analysis teams, research or business units
Industry UsageDeveloping AI models, creating generative content, NLP applicationsAnalyzing data, building predictive models, informing business decisions

Remote Generative Ai specialists focus on creating AI models that generate content, requiring expertise in AI/ML and programming. Data Scientists analyze data to extract insights and build models, often with similar technical backgrounds. While both roles may work remotely and in tech industries, their core functions differ: one develops generative AI systems, the other interprets data for strategic insights.

Can you work in AI remotely?

Remote Generative AI roles are common in the industry, allowing professionals to work from various locations. These jobs typically require strong skills in machine learning, programming, and familiarity with AI tools, and often involve collaboration through online platforms. Many companies offer flexible schedules and remote work arrangements for AI specialists.

What is a Remote Generative AI job?

A Remote Generative AI job involves working with artificial intelligence systems that can create new content, such as text, images, or music, from data. These roles are performed remotely, allowing professionals to work from anywhere while developing, training, and deploying generative models like GPT or DALL-E. Job responsibilities may include data preparation, model training, evaluation, and integrating generative AI solutions into products or services. Professionals in this field often collaborate with teams online using cloud-based tools and communication platforms.
What are popular job titles related to Remote Generative Ai jobs in Alaska? For Remote Generative Ai jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Remote Generative Ai jobs in Alaska look for? The top searched job categories for Remote Generative Ai jobs in Alaska are:
What cities in Alaska are hiring for Remote Generative Ai jobs? Cities in Alaska with the most Remote Generative Ai job openings:
Remote Generative Ai jobs near you
Infographic showing various Remote Generative Ai job openings in Alaska as of July 2026, with employment types broken down into 77% Full Time, and 23% Part Time. Highlights an 100% Remote job distribution.
Data Engineer AI

Data Engineer AI

Sedgwick

Minto, AK • On-site, Remote

$118K - $142K/yr

Other

Posted 14 days ago

Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 318 frontline employees who took The Breakroom Quiz

203rd of 298 rated insurance

Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work

Fortune Best Workplaces in Financial Services & Insurance

Data Engineer AI

Role Overview

As a Senior Data Engineer within the Transformation Office, you are the hands-on architect of the data supply chain for our most advanced initiatives. You will be responsible for the "heavy lifting" required to fuel Data Science models and AI applications with high-fidelity data. Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL Server, DB2) with our modern Snowflake environment and AWS/Azure AI stacks. You are a "day-one" builder who ensures that data is not just moved, but engineered for the specific requirements of model training, feature stores, and RAG-based AI systems.

Key Responsibilities

Hybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI services.

Engineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid data.

Engineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and Azure.

Snowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optimization to support high-concurrency AI workloads.

Legacy "Back-Reach" Engineering: Execute non-invasive data extraction patterns to unlock mission-critical data from decades-old on-premise systems without disrupting core business operations.

Multi-Cloud Orchestration: Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory, ensuring the synchronization of data across our multi-cloud AI posture.

IT & Security Diplomacy: Partner directly with central IT, Database Administrators, and Security teams to solve connectivity hurdles (PrivateLink, IAM, firewalls) and secure "license to operate" for new data flows.

Data Quality for Model Integrity: Implement automated validation and observability layers to detect data drift and quality issues that could compromise the accuracy of production AI and Data Science models.

Cost & Performance Management: Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake, AWS, and Azure to manage the ROI of the Transformation Office.

Direct Stakeholder Collaboration: Work as a dedicated engineering partner to MLOps and Data Science teams to rapidly iterate on data requirements for evolving AI use cases.

Qualifications

Education: Bachelor's degree in Computer Science, Data Engineering, or a related field is required. A Master's degree is highly desirable.

Proven Execution: 6+ years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments.

Snowflake Mastery: Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services.

Multi-Cloud Proficiency: Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services.

Technical Stack: Mastery of Python, SQL, and PySpark. Deep experience with data orchestration and containerization (Docker).

Legacy Expertise: Proven ability to interface with "old world" tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption.

AI/DS Fluency: A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines).

Execution Mindset: A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office.

#LI-TS1 #remote

Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

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