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Remote Generative Ai Engineer Jobs in Salem, MA (NOW HIRING)

This role focuses on creating novel techniques and approaches for discriminative and generative AI ... REMOTE - This position is remote. The candidate is able to work remotely from any location. They ...

Remote Job Overview We are seeking experienced Enterprise Marketing & Content Experts to evaluate ... Professional experience using generative AI or AI agents. * Strong analytical, problem-solving, and ...

Remote Job Overview We are seeking experienced Enterprise Marketing & Content Experts to evaluate ... Professional experience using generative AI or AI agents. * Strong analytical, problem-solving, and ...

Remote Job Overview We are seeking experienced Business Intelligence & Analytics Experts to ... Experience using generative AI or AI agents in professional workflows. * Experience integrating BI ...

Remote Job Overview We are seeking experienced Business Intelligence & Analytics Experts to ... Experience using generative AI or AI agents in professional workflows. * Experience integrating BI ...

Join a cutting-edge AI Platform team as a Senior Data Scientist in a 6-month remote contract-to ... and Generative AI applications · Hands-on experience designing and deploying RAG systems · ...

Showing results 21-40

Remote Generative Ai Engineer information

See Salem, MA salary details

$41.5K

$126.6K

$209.2K

How much do remote generative ai engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote generative ai engineer in Salem, MA is $126,603.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,700.00 and $165,500.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

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

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

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

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What are popular job titles related to Remote Generative Ai Engineer jobs in Salem, MA?

For Remote Generative Ai Engineer jobs in Salem, MA, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Engineer jobs in Salem, MA look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Salem, MA are:

What cities near Salem, MA are hiring for Remote Generative Ai Engineer jobs?

Cities near Salem, MA with the most Remote Generative Ai Engineer job openings:

Infographic showing various Remote Generative Ai Engineer job openings in Salem, MA as of August 2026, with employment types broken down into 76% Full Time, 19% Part Time, and 5% Contract. Highlights an 71% Physical, 4% Hybrid, and 25% Remote job distribution, with an average salary of $126,603 per year, or $60.9 per hour.

Principal AI Engineering Architect

The Mutual Group

Boston, MA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 23 days ago


Key responsibilities

  • Define architecture patterns and technical standards for AI-enabled applications, components, and workflows.

  • Provide hands-on architecture leadership in design reviews, technical decision-making, and implementation planning.

  • Design reusable platform patterns and integration methods for connecting AI capabilities with enterprise systems and data sources.


Job description

Department:

Information Technology

Job Description:

As the Principal AI Engineering Architect, you will play a key role in supporting The Mutual Group (TMG), GuideOne Insurance, and future members by defining and guiding the technical architecture for AI-first engineering, secure AI platforms, reusable components, integration patterns, and scalable technical standards across TMG. This is a senior individual contributor role for a deeply technical architect who can translate complex business and technology needs into practical, secure, and reusable AI-enabled solutions.

This role will work across AI-First IT, Applications, Engineering, Data, Infrastructure, Operations, Security, Architecture, and business teams to design AI capabilities that can move from concept to production with the right architecture, controls, integration model, and operational readiness. The Principal AI Engineering Architect will be expected to stay close to the work, review designs, guide engineering teams, solve difficult technical problems, and create patterns that can be reused across multiple initiatives.

The role will have deeper focus on AI-enabled business processes and AI-first future platforms, while also supporting AI adoption across the IT SDLC and IT operations. The successful candidate will bring strong technical judgment, hands-on architecture depth, and the ability to simplify complex AI engineering concepts into standards, blueprints, and implementation guidance that broader teams can adopt.

Work Arrangement:

  • Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in-office schedule. The initial training period may require additional inoffice days.

Accountabilities:

Architecture Strategy & Technical Direction

  • Define architecture patterns and technical standards for AI-enabled applications, copilots, intelligent workflows, automation agents, enterprise knowledge solutions, and reusable AI components.

  • Translate business and technology use cases into scalable solution architectures, including application design, data flows, integration patterns, model usage, security controls, and operational requirements.

  • Partner with the Sr. Director, AI Platform and Engineering to shape platform architecture, technical roadmaps, reference implementations, and engineering playbooks.

  • Provide hands-on architecture leadership in design reviews, technical decision-making, proof-of-concept evaluation, implementation planning, and production readiness.

  • Stay current on emerging AI engineering patterns, GenAI platforms, agent frameworks, model orchestration, cloud AI services, enterprise knowledge systems, and secure deployment practices.

AI Platform Architecture & Reusable Engineering Patterns

  • Design reusable platform patterns for model access, retrieval-augmented generation, vector databases, semantic search, embeddings, enterprise knowledge integration, prompt and response handling, and AI observability.

  • Define integration patterns for connecting AI capabilities with enterprise systems, APIs, data platforms, document repositories, workflow tools, service management platforms, and business applications.

  • Create architecture blueprints, technical standards, reusable components, templates, and implementation guidance that improve speed, consistency, quality, and reuse.

  • Guide decisions on build versus buy, platform selection, vendor capabilities, interoperability, scalability, maintainability, and cost effectiveness.

  • Ensure AI platform patterns are designed for secure production use, including reliability, monitoring, access control, auditability, and lifecycle management.

GenAI, Agentic AI & Model Engineering

  • Guide implementation of Generative AI solutions using LLMs, SLMs, embeddings, prompt engineering, RAG, semantic search, summarization, classification, extraction, and enterprise knowledge retrieval.

  • Define technical patterns for Agentic AI, including tool and function calling, workflow orchestration, human-in-the-loop controls, context management, memory patterns, guardrails, monitoring, and safe execution.

  • Establish usage patterns for Model Context Protocol (MCP) or similar approaches for securely connecting AI systems to enterprise tools, data sources, APIs, and workflow actions.

  • Support practices for model selection, experimentation, evaluation, validation, performance monitoring, drift detection, feedback loops, and responsible production deployment.

  • Help engineering teams design AI solutions that are accurate, observable, explainable where appropriate, cost-aware, and aligned with business and risk expectations.

Business Solution Architecture & Enterprise Adoption

  • Partner with business, product, data, and technology teams to design AI-enabled solutions for underwriting, claims, operations, finance, customer service, and other enterprise functions.

  • Translate business needs into practical AI architectures for decision support, workflow automation, document intelligence, knowledge assistance, triage, summarization, and productivity improvement.

  • Help teams evaluate feasibility, data readiness, integration complexity, user experience, human oversight, and operational support requirements.

  • Create reusable patterns that allow similar AI capabilities to be deployed across multiple business processes with less rework.

  • Communicate architecture decisions clearly to technical and non-technical stakeholders, including tradeoffs, risks, dependencies, and implementation options.

Security, Governance & Engineering Quality

  • Partner with Security, Data, Architecture, and AI & Technology Risk Governance teams to embed secure-by-design, privacy-by-design, and responsible AI practices into solution architecture.

  • Define technical controls for identity and access management, sensitive data handling, prompt and response logging, output validation, human oversight, vendor integration, and production readiness.

  • Ensure AI solutions align with enterprise standards for security, privacy, auditability, observability, resilience, compliance, and operational support.

  • Participate in architecture governance, design reviews, technical risk assessments, and production readiness reviews.

  • Promote engineering quality through strong documentation, testability, traceability, performance considerations, and clear support models.

Qualifications:

  • 10+ years of progressive technology experience across software engineering, architecture, platform engineering, cloud, data, integration, automation, AI, or enterprise technology delivery.

  • 5+ years of experience with AI, machine learning, automation, advanced analytics, intelligent platforms, developer productivity tools, or emerging technology capabilities.

  • Strong technical depth in Generative AI patterns, including LLMs, SLMs, embeddings, prompt engineering, RAG, vector databases, semantic search, evaluation frameworks, and enterprise knowledge integration.

  • Experience with Agentic AI patterns, including agents, tool/function calling, orchestration, human-in-the-loop workflows, context management, guardrails, monitoring, and safe deployment.

  • Familiarity with Model Context Protocol (MCP) or similar approaches for securely connecting AI systems to enterprise tools, data sources, APIs, and workflow actions.

  • Strong understanding of modern architecture patterns, including APIs, microservices, event-driven design, cloud-native platforms, data integration, DevSecOps, CI/CD, observability, cybersecurity, identity, and privacy.

  • Proven experience designing production-grade enterprise platforms, reusable architecture patterns, integration frameworks, automation capabilities, or developer productivity solutions.

  • Experience working in regulated environments with security, privacy, risk, compliance, auditability, and operational readiness expectations preferred.

  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field required. Master's degree preferred.

Leadership Attributes

  • Deeply technical architect who can dive into details while keeping architecture practical, scalable, and business aligned.

  • Strong systems thinker who simplifies complexity into reusable patterns, standards, and clear technical guidance.

  • Hands-on problem solver with strong analytical reasoning and sound judgment.

  • Collaborative partner who builds trust across business, engineering, data, security, infrastructure, operations, and governance teams.

  • Constructive challenger who raises technical standards while helping teams move quickly and responsibly.

  • Strong communicator who can explain complex AI and architecture concepts in clear, actionable terms.

Pay Range:

Anticipated Hiring Range:

  • $170,000 - $210,000annual base salary depending on experience, qualifications, and geographic location

Benefits:

We are proud to offer our full-time regular employees a robust benefits suite that includes:

  • Competitive base salary plus incentive plans for eligible team members

  • 401(K) retirement plan that includes a company match of up to 6% of your eligible salary

  • Free basic life and AD&D, long-term disability and short-term disability insurance

  • Medical, dental and vision plans to meet your unique healthcare needs

  • Wellness incentives

  • Generous time off program that includes personal, holiday and volunteer paid time off

  • Flexible work schedules and hybrid/remote options for eligible positions

  • Educational assistance

Equal Opportunity Employer

The Mutual Groupis an Equal Opportunity Employer. It is our policy to recruit, hire, train and promote individuals in all job classifications without regard to race, color, religion, sex, national origin, age, veteran status, disability, sexual orientation, gender identity or any other characteristic protected by law.

  • Know Your Rights: Workplace Discrimination is Illegal

  • Your Rights Under USERRA

Applicants requiring a reasonable accommodation due to a disability at any stage of the employment application process should contactTalent@themutualgroup.com.

Employment Verification

The Mutual Group participates in theE-Verifyprogram and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. You are protected fromemployment discriminationbased on your citizenship status and national origin.

E-Verify Program Overview

E-Verify Participation Poster

All offers of employment are contingent upon the successful completion of a background check.

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