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Remote Generative Ai Engineer Jobs in Washington

Rios Partners

AI Engineer

Arlington, VA · On-site +1

$100K - $110K/yr

Write and maintain documentation with the aid of generative AI tools.Collaboration & Continuous ... Strong programming skills in Python or JavaScript/TypeScript.Familiarity with LLM concepts (tokens ...

Interon IT Solutions

AI Product Owner

Chantilly, VA · Remote

Remote Employment Type: W2 Industry: Healthcare We are seeking an experienced AI Product Owner to ... Collaborate with AI/ML engineers, data scientists, and architects throughout the AI product ...

Mondo

AI Product Manager

Centreville, VA · Remote

$140K - $150K/yr

AI Product Manager Location-Type: Remote (U.S. Based) Start Date Is: ASAP Employment Type ... This individual will partner closely with customers, Product leadership, AI engineers, and cross ...

Relativity

Software Engineer

Washington, DC · On-site +1

Posting Type Hybrid/Remote Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Experience working with large language model (LLM) APIs or generative AI systems * Experience ...

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Remote Generative Ai Engineer information

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 the most commonly searched types of Generative Ai Engineer jobs in Washington?

The most popular types of Generative Ai Engineer jobs in Washington are:

What are popular job titles related to Remote Generative Ai Engineer jobs in Washington?

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

What job categories do people searching Remote Generative Ai Engineer jobs in Washington look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Washington are:

What cities in Washington are hiring for Remote Generative Ai Engineer jobs?

Cities in Washington with the most Remote Generative Ai Engineer job openings:

Remote Generative Ai Engineer jobs near you
Infographic showing various Remote Generative Ai Engineer job openings in Washington as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.

Cloud/AI Engineer

Strategic Innovation Group LLC

Arlington, VA • Remote

$64.25 - $85.75/hr

Full-time

Dental, Vision, Life, Retirement

Re-posted 26 days ago

Job description

Strategic Innovation Group (SIG) is seeking a Cloud/AI Engineer to design, develop, and deploy secure, scalable cloud-native and artificial intelligence solutions supporting Federal Aviation Administration (FAA) programs. This role serves as a senior technical leader responsible for modernizing legacy systems, architecting enterprise cloud platforms, developing production-grade AI applications, and implementing Generative AI capabilities including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI solutions. The successful candidate will collaborate closely with government stakeholders, product teams, and engineering staff to deliver innovative, mission-critical technologies that improve operational efficiency, enable data-driven decision-making, and advance the FAA's digital transformation initiatives while meeting stringent security, compliance, and governance requirements.

SIG is a fast growing 8(a) government contractor based in Arlington, Virginia. We offer a broad range of technical expertise and experience in Digital Transformation, Data Management/Data Science, and Systems Modernization. At SIG, our people are our mission. Come join our team! A successful candidate will be offered the following:

Greatwork/life balance
Eligibilityforperformance-basedparticipationincashbonuses
Potential toparticipatein growth of the company through incentives
Excellent benefits,includinghealth, dental, vision,generousPTO, a 401(k) with match, life insurance, short- and long-term disability,anda health savings account (HSA)
Additionally, this position is expected to be generally remote, with occasional visits to the office and client facilities in the Washington, DC metropolitan area as needed.

ESSENTIAL DUTIES AND RESPONSIBILITIES

The essential functions include, but are not limited to the following:

  • Lead the design, development, deployment, and sustainment of secure, scalable cloud and AI solutions supporting FAA mission objectives.
  • Collaborate with government stakeholders to translate business requirements into innovative, mission-focused technology solutions.
  • Lead the modernization of legacy systems and enterprise platforms through cloud transformation and application modernization initiatives.
  • Establish and promote architecture, engineering, security, and software development best practices across project teams.
  • Provide technical leadership, mentoring, and guidance to engineering teams while supporting Agile project delivery.
  • Ensure solutions meet federal security, governance, compliance, and operational requirements throughout the system lifecycle.
  • Develop and maintain technical documentation, architecture artifacts, and implementation plans to support operations and compliance.
  • Evaluate emerging technologies, resolve complex technical challenges, and recommend improvements that enhance performance, reliability, and mission outcomes.
  • Perform other duties as assigned.

REQUIRED EXPERIENCE/QUALIFICATIONS

  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • Cloud Engineer experience: 15+ years
  • AI Engineer experience: 1+ years
  • Experience delivering enterprise-scale technology solutions across public-sector and private-sector organizations, including highly ambiguous environments requiring problem discovery, requirements definition, and solution development.
  • Hands-on experience in cloud engineering, cloud-based application development, and full stack software engineering.
  • Proven track record designing, building, deploying, and operating production-grade applications spanning front-end interfaces, backend services, and cloud data platforms.
  • Experience migrating legacy on-premises systems to the cloud and refactoring monolithic legacy codebases into microservices architectures and cloud-native tooling, using Docker, Kubernetes, serverless services, and cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience leading or executing migrations from on-premises data warehouses to cloud-based data warehouse platforms (e.g., Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse), including data pipeline redesign, schema conversion, and validation of data integrity throughout the migration.
  • Strong proficiency in Python, JavaScript/TypeScript, React, FastAPI, SQL, Spark/PySpark, REST APIs, and modern software development frameworks.
  • Expertise implementing CI/CD pipelines, DevOps practices, infrastructure automation (e.g., Terraform, CloudFormation), and platform engineering principles to support scalable cloud delivery.
  • Experience integrating enterprise systems through APIs, event-driven architectures, workflow orchestration platforms, and distributed services.
    Strong understanding of software engineering fundamentals, distributed systems, cloud architecture, and cloud application engineering best practices.
  • Demonstrated ability to architect secure, scalable, and resilient cloud systems with attention to governance, auditability, data protection, and access controls.
  • Hands-on experience developing and deploying Generative AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI systems, semantic search, and vector databases, integrated into cloud-native application architectures.
  • Experience managing the AI application lifecycle within cloud environments, including data ingestion, model integration, deployment, monitoring, observability, and continuous improvement using cloud-native MLOps tooling.
  • Proven ability to collaborate with business stakeholders, product teams, and technical leadership to translate business requirements into scalable technical solutions and AI-enabled products.
  • Experience delivering mission-critical applications in regulated, compliance-sensitive, or enterprise environments.
  • Strong analytical, problem-solving, and systems-thinking skills with the ability to identify operational challenges and develop technology solutions that deliver measurable business value.


PREFERRED EXPERIENCE/QUALIFICATIONS

  • Prior experience in federal contracting or highly regulated enterprise environments.
  • Active FAA clearance


SPECIAL REQUIREMENTS/SECURITY CLEARANCE

Must have ability to obtain a Public Trust clearance

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