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Full Stack Ai Engineer Jobs in Washington, DC (NOW HIRING)

ECS

Senior Full Stack AI Developer

Fairfax, VA · On-site

$125K - $185K/yr

Everforth ECS is seeking an Senior Full Stack AI Developer to work remotely . We are looking for a talented Senior Full Stack AI Developer, who is passionate about development and engineering with ...

Fortegra

Senior Full Stack AI Engineer

Washington, DC · On-site

We are seeking Full Stack Engineers who thrive in fast-moving environments to design, build, and deploy enterprise-grade applications while leveraging AI-driven development tools. Responsibilities ...

Dark Wolf Solutions

Full Stack AI Developer

Mclean, VA · On-site

We are seeking a highly motivated and self-directed professional to fill the role of Full-Stack AI ... Engineer and scale AI-driven platforms to streamline data ingestion, exploration, triage, and ...

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All JobsFull Stack Ai Engineer JobsFull Stack Ai Engineer Jobs in Washington, DC

Full Stack Ai Engineer information

See Washington, DC salary details

$50.3K

$152.2K

$215.1K

How much do full stack ai engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for full stack ai engineer in Washington, DC is $152,184.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $178,400.00 per year, depending on experience, location, and employer.

What is a Full Stack AI Engineer?

A Full Stack AI Engineer is a professional who develops and deploys artificial intelligence solutions across both the front-end and back-end of applications. They combine expertise in AI and machine learning with software engineering skills, allowing them to build, integrate, and maintain AI-powered features throughout the entire technology stack. Their responsibilities often include designing machine learning models, integrating them with APIs, and ensuring seamless user experiences on web or mobile platforms. Full Stack AI Engineers bridge the gap between data science and software development, enabling scalable and production-ready AI applications.

How do Full Stack AI Engineers typically collaborate with data scientists and front-end developers on AI-driven projects?

Full Stack AI Engineers often serve as the bridge between data scientists, who develop machine learning models, and front-end developers, who build user interfaces. They work closely with data scientists to understand the model requirements and deployment needs, and with front-end teams to ensure seamless integration of AI functionalities into applications. This collaboration requires effective communication skills and a clear understanding of both the technical and user experience aspects. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth teamwork and successful project outcomes.

What are the key skills and qualifications needed to thrive as a Full Stack AI Engineer, and why are they important?

To thrive as a Full Stack AI Engineer, you need strong programming skills (such as Python, JavaScript), understanding of machine learning algorithms, and experience with both front-end and back-end development, often supported by a degree in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and containerization tools (Docker, Kubernetes) is typically required. Excellent problem-solving abilities, collaboration, and effective communication are standout soft skills in this role. These skills and qualifications enable the seamless integration of AI models into scalable applications, ensuring innovative and robust solutions.
What are popular job titles related to Full Stack Ai Engineer jobs in Washington, DC? For Full Stack Ai Engineer jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Full Stack Ai Engineer jobs in Washington, DC look for? The top searched job categories for Full Stack Ai Engineer jobs in Washington, DC are:
Full Stack Ai Engineer jobs near you
Infographic showing various Full Stack Ai Engineer job openings in Washington, DC as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $152,184 per year, or $73.2 per hour.

Senior Full Stack AI Developer

ECS

Fairfax, VA • On-site

$125K - $185K/yr

Full-time

Posted 4 days ago

Job description

Everforth ECS is seeking an Senior Full Stack AI Developer to work remotely.
We are looking for a talented Senior Full Stack AI Developer, who is passionate about development and engineering with data, cloud, and AI. Strong candidates will have a desire to learn and work with new technologies, while providing high quality technical support and leadership for transformational development efforts.
Responsibilities:
  • Building quality solutions that solve real world problems using a high level of machine intelligence
  • Finding intelligent ways to solve problems without a lot of repeat work
  • Leveraging expertise to advise and create solutions that are simple, secure, and maintainable
  • Build, maintain, and update automation code and/or scripts
  • Design and implement continuous integration and delivery automation in support of software, configuration, and infrastructure management
  • Development of microservices and applications
  • Finding opportunities to use data and metrics to inform decisions and create changes to improve the environment
  • You will be supporting Commercial Accounts (Not Federal)

Salary: $125,000 - $185,000
General Description of Benefits
Required Skills:
  • Bachelor's degree in engineering or technical discipline, or associates with equivalent years of experience.
  • At Least 8 Years of overall experience and knowledge of:
    • Unix/Linux Administration
    • Networking and virtual infrastructure management
    • Application Development
    • Strong scripting in at least one language Python, Perl, Shell, Batch
    • Cloud Engineering
    • AI/ML concepts including large language models, retrieval-augmented generation, vector databases, and model deployment pipelines.
  • Must successfully complete a stringent Background Investigation.

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