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Generative Ai Developer Jobs in Ashburn, VA (NOW HIRING)

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AI-Native Software Engineer

Arlington, VA · On-site

$140 - $190/hr

Prototype and evaluate emerging AI developer tooling (agent frameworks, code copilots, automated testing agents) * Mentor engineering teams on effective use of generative AI in development workflows

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How much do generative ai developer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for generative ai developer in Ashburn, VA is $46.31, according to ZipRecruiter salary data. Most workers in this role earn between $24.09 and $56.06 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

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

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

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

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Ashburn, VA?

For Generative Ai Developer jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Ashburn, VA look for?

The top searched job categories for Generative Ai Developer jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Generative Ai Developer jobs?

Cities near Ashburn, VA with the most Generative Ai Developer job openings:

Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Ashburn, VA as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $96,329 per year, or $46.3 per hour.

Generative AI Engineer Role

OpenDataJobs

Washington, DC • On-site

Full-time

Posted 12 days ago

Job description

The work
Generative AI Engineers build production applications around foundation models and large language models. They turn model capabilities into tools for search, drafting, summarization, information extraction, multimodal work, and guided action, with the controls and evidence needed to understand how those tools behave.
The role concentrates on application and context engineering. Generative AI Engineers connect models to authoritative knowledge, tools, and workflows; design prompts and structured outputs; evaluate quality, grounding, safety, security, latency, and cost; and monitor the application after release. They treat fluent output as something to test, not proof that the system is correct.
What you'll build
• Grounded assistants and knowledge applications with retrieval-augmented generation (RAG), hybrid or vector search, citations, metadata filtering, and source-level access controls.
• Drafting, summarization, classification, extraction, and transformation services exposed through user interfaces or APIs.
• Agents and multistep workflows with defined tool schemas, constrained permissions, approval gates, memory boundaries, replay, and exception handling.
• Evaluation systems with curated test cases, task-specific rubrics, retrieval measures, grounding checks, safety and security tests, and regression thresholds.
• Operational pipelines for versioning prompts and configurations, comparing models, tracing execution, monitoring quality and cost, collecting feedback, and responding to incidents.
Who you are
You are an application engineer who can work with fast-moving model capabilities without chasing every new release. You choose architectures by evidence, make uncertainty visible, and separate a convincing demonstration from a dependable service.
You think in complete workflows: sources, context, models, tools, permissions, people, and failure paths. You collaborate with domain experts, data and software engineers, security and privacy specialists, and accountable owners to decide where generation helps and where deterministic methods or human judgment should remain in control.
What you bring
• A strong application-engineering foundation, including programming, APIs, testing, version control, service integration, and production debugging.
• Practical experience with foundation-model integration, prompt and context design, structured outputs, model selection, and failure analysis.
• Working knowledge of retrieval systems, embeddings, search, knowledge stores, document ingestion, and data-access controls.
• Evaluation discipline across answer quality, retrieval relevance, grounding, safety, security, latency, cost, and user outcomes.
• The judgment to constrain tools and agents, design human-review paths, document limitations, and respond when production behavior changes.
About OPEN Data Jobs
OPEN Data Jobs connects AI, data, and software professionals with critical roles, primarily in the federal sector. Registering with ODJ can put your profile in view for multiple positions across several clients.
Register for Generative AI Engineer Role
Click Apply below to register for Generative AI Engineer Role.
Requirements
What openings may require
An opening may emphasize enterprise search, document intelligence, multimodal applications, code generation, contact-center support, agent workflows, model adaptation, synthetic data, or evaluation and red-team engineering. Building or training a foundation model from scratch is not a universal requirement.
Specific openings may name a model provider, cloud platform, vector or search service, agent framework, observability stack, programming language, model-evaluation approach, content-safety service, or security and governance framework. OPEN Data Jobs will state which capabilities are required and which are preferred.
Benefits
Compensation, benefits, work location, and employment terms are set for each specific opening and will be stated with that opening

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