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Ai Content Engineer Jobs in Springfield, VA (NOW HIRING)

Senior AI Defense Engineer

Washington, DC

$129K - $177K/yr

Identify and document AI-specific threats with emphasis on how vendor controls (gateways, content ... AI Defense Engineering - Evaluate and operationalize security controls, guardrails, and enforcement ...

Senior AI Defense Engineer

Washington, DC

$129K - $177K/yr

Identify and document AI-specific threats with emphasis on how vendor controls (gateways, content ... AI Defense Engineering - Evaluate and operationalize security controls, guardrails, and enforcement ...

Senior AI Defense Engineer

Washington, DC · On-site

$129K - $177K/yr

Identify and document AI-specific threats with emphasis on how vendor controls (gateways, content ... AI Defense Engineering - Evaluate and operationalize security controls, guardrails, and enforcement ...

AI Engineer

Mclean, VA · On-site

$98K - $163K/yr

Contribute to demos, technical documentation, and solution content for proposals and pitch ... Certifications in cloud architecture, DevOps, or AI/ML (e.g., AWS/Azure/GCP, Databricks, Kubernetes)

AI Engineer

Mclean, VA · On-site

$98K - $163K/yr

Contribute to demos, technical documentation, and solution content for proposals and pitch ... Certifications in cloud architecture, DevOps, or AI/ML (e.g., AWS/Azure/GCP, Databricks, Kubernetes)

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

Lead AI Engineer 3 days onsite in Rockville, MD Long Term Contract Must be willing to interview ... Develop LLM-driven compliance reasoning and scalable RAG grounded in regulatory content.

New

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

Lead AI Engineer 3 days onsite in Rockville, MD Long Term Contract Must be willing to interview ... Develop LLM-driven compliance reasoning and scalable RAG grounded in regulatory content.

New

Software Engineer, Applied AI

Washington, DC · On-site

$165K - $250K/yr

We are hiring a Software Engineer, Applied AI to join our team located in Washington, DC. As the ... Develop next generation algorithms to understand visual and textual content along with user ...

Salary: Support Engineer Content Guru is a leading global provider of enterprise cloud Customer Experience (CX) and contact centre solutions, and we are at the forefront of the Generative AI ...

Digital Content Specialist

Fairfax, VA · On-site

$56K/yr

Digital Content Specialist Onsite 4 days/week in Fairfax, VA (Mosaic District) to start, further ... AI solutions, Cloud Migrations, custom web app development, data analytics/big data and DevOps. We ...

New

Support Engineer Content Guru is a leading global provider of enterprise cloud Customer Experience (CX) and contact centre solutions, and we are at the forefront of the Generative AI evolution. We're ...

Support Engineer Content Guru is a leading global provider of enterprise cloud Customer Experience (CX) and contact centre solutions, and we are at the forefront of the Generative AI evolution. We're ...

Showing results 41-60

Ai Content Engineer information

See Springfield, VA salary details

$30.8K

$121.8K

$134.7K

How much do ai content engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for ai content engineer in Springfield, VA is $121,808.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,500.00 and $133,700.00 per year, depending on experience, location, and employer.

What are some typical challenges an AI content engineer faces when deploying AI-generated content at scale?

AI Content Engineers often encounter challenges related to maintaining content quality and consistency when deploying AI-generated material across multiple platforms. Balancing automation with human oversight is crucial to avoid errors, biases, or brand voice inconsistencies. Additionally, integrating AI tools with existing content management systems and ensuring compliance with data privacy regulations can be complex. Close collaboration with data scientists, content strategists, and legal teams is often required to address these issues effectively.

What is the difference between Ai Content Engineer vs Data Scientist?

AspectAi Content EngineerData Scientist
Required CredentialsBachelor's in Computer Science, AI, or related fields; experience with NLP and ML toolsBachelor's or higher in Data Science, Statistics, or related fields; proficiency in programming and statistical analysis
Work EnvironmentDeveloping AI models for content generation, working with NLP and ML frameworksAnalyzing data sets, building predictive models, interpreting complex data
Employer & Industry UsageTech companies, content platforms, AI startupsFinance, healthcare, tech firms, research institutions

While both roles involve AI and data analysis, Ai Content Engineers focus on creating AI systems for content generation, whereas Data Scientists analyze data to derive insights and build predictive models. The roles often overlap in skills but differ in primary objectives and applications.

What is an AI content engineer?

An AI Content Engineer is a professional who designs, develops, and manages content systems powered by artificial intelligence. They work at the intersection of content strategy, data science, and machine learning, creating tools and workflows that automate or enhance content creation, curation, and personalization. Their responsibilities often include training language models, integrating AI capabilities into content management systems, and ensuring the quality and relevance of AI-generated content. This role is crucial for organizations aiming to scale content production while maintaining quality and consistency.

What are the key skills and qualifications needed to thrive as an AI content engineer?

To thrive as an AI Content Engineer, you need a strong background in computer science, natural language processing (NLP), and experience with programming languages like Python, as well as a relevant degree or equivalent experience. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), NLP libraries (like spaCy or NLTK), and cloud platforms is typically required. Creativity, problem-solving, and effective communication are essential soft skills for designing user-focused AI content solutions and collaborating with cross-functional teams. These skills ensure the development of robust, innovative AI-driven content systems that meet business and user needs.
What are popular job titles related to Ai Content Engineer jobs in Springfield, VA? For Ai Content Engineer jobs in Springfield, VA, the most frequently searched job titles are:
What job categories do people searching Ai Content Engineer jobs in Springfield, VA look for? The top searched job categories for Ai Content Engineer jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Ai Content Engineer jobs? Cities near Springfield, VA with the most Ai Content Engineer job openings:
Infographic showing various Ai Content Engineer job openings in Springfield, VA as of August 2026, with employment types broken down into 71% Full Time, 26% Part Time, and 3% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $121,808 per year, or $58.6 per hour.

Senior AI Defense Engineer

Wilmerhale

Washington, DC

$129K - $177K/yr

Full-time

Re-posted just now


Job description

WilmerHale is a leading, full-service international law firm with 1,000 lawyers located throughout 12 offices in the United States and Europe. Our lawyers work at the intersection of government, technology and business, and we remain committed to our guiding principles of providing quality, excellent legal and client services; developing diversity among our lawyers and staff and cultivating an environment that promotes an ambitious spirit, collaboration and collegiality by drawing on the extraordinary talents and dynamic experience of our lawyers. Our goal is to reflect the diversity of our clients and the communities in which we practice.

 About the Role

The Senior AI Defense Engineer is a technical leader responsible for securing AI in a global law firm environment. This role is responsible for setting technical direction, driving delivery, and mentoring colleagues to raise their awareness and capabilities. The role will translate emerging AI threats into practical defenses, guardrails, policy enforcement layers, monitoring and detections, adversarial test automation, and hardened environments that hold up under real attacker pressure.

The role will support a smart-integration, buy-before-build, security strategy. You will evaluate, select, and operationalize commercial Al security solutions that meet stringent legal-sector expectations, including matter confidentiality, ethical walls, client audit requirements, data residency constraints, and contractual information technology service obligations.

Success looks like: The role also enables progress by enhancing and performing commercial AI tool evaluations and approvals, assessing internally developed AI solutions, and responding to growing audit demands with credible evidence of AI cybersecurity protections. Additionally, success includes secure-by-default adopted by engineering teams; adversarial evaluation and assessments that reliably finds issues before production; telemetry and detections that catch abuse early; and an AI security roadmap that stays current with fast-moving technology shifts.

What You Will Be Doing

  • Threat Modeling & Risk Assessment - Guide and conduct technical threat modeling for AI/ML systems (neural networks, expert systems, retrieval-augmented generation, classification models, etc.). Identify and document AI-specific threats with emphasis on how vendor controls (gateways, content filters, policy engines, etc.) mitigate prompt injection, data leakage, jailbreaks, and unsafe autonomy. Provide clear, prioritized mitigation guidance to colleagues via vendor configuration standards, reference patterns, and exception processes.
  • AI Defense Engineering - Evaluate and operationalize security controls, guardrails, and enforcement mechanisms for AI services (e.g., input/output filters, policy enforcement layers, content safety checks, rate limiting, abuse detection). Enable detections and monitoring for AI-specific attack patterns using logs, telemetry, and model signals. Work with platform teams to secure the integration and operational use of enterprise AI services, including protection of credentials, data flows, storage, and access controls across Copilot and other commercial LLM platforms.     
  • Adversarial Testing & Red Teaming - Identify and utilize adversarial test suites for AI applications (prompt libraries, fuzzing harnesses, automated attack campaigns). Simulate realistic attacker behavior targeting AI endpoints and agents, capture and track issues as actionable vulnerabilities. Partner with application and product teams to validate fixes, re-test, and track residual risk.
  • Tooling & Automation -Ensure AI capabilities are incorporated into the existing and future security stacks (SIEM, SOAR, EDR, WAF, API gateways, identity platforms).
  • Incident Response & Forensics for AI Systems - Serve as technical lead for security incidents that involve AI services (e.g., abuse, data exfiltration via AI systems, compromised API keys, poisoned training data). Analyze logs and model behavior to reconstruct attack paths and define durable fixes. Improve playbooks/runbooks and lead post-incident technical reviews.
  • Collaboration - Serve as the AI security technical lead with engineering, product, infrastructure, and security leadership. Communicate tradeoffs clearly, align stakeholders, and unblock delivery. Provide technical input into AI security standards and guidelines, staying grounded in implementation and operational constraints along with emphasizing vendor capability fit, maintainability, and total cost of ownership (TCO).
  • Roadmap Leadership - Own the technical strategy and roadmap for AI security engineering. Translate threat intelligence and risk assessments into prioritized engineering work, milestones, and measurable outcomes. Lead technical design reviews, set standards for secure AI architecture, and ensure high-quality implementation, supportability, and operational readiness.
  • Contributes to the Firm's Service Matters initiative to consistently improve its image internally and externally.  Displays professionalism, quality service and a "can do" attitude to internal members/departments of the Firm as well as external clients and vendors via electronic and print correspondence, over the telephone and in-person.