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Chatbot Training Jobs in Virginia (NOW HIRING)

Senior Director, Software Engineering

Mclean, VA · On-site

$259K/yr

Own delivery for internal AI chatbot and GenAI services: roadmap execution, sprint planning ... training programs. CA Applicants: Qualified applications with arrest or conviction records will be ...

Senior Director, Software Engineering

Mclean, VA · On-site

$255K/yr

Own delivery for internal AI chatbot and GenAI services: roadmap execution, sprint planning ... training programs. CA Applicants: Qualified applications with arrest or conviction records will be ...

Coordinate and deliver 12-24 annual training sessions through webinars, phone, in-person, and group ... Conduct quality control and testing on taxonomy tagging, AI search, chatbot content, and search ...

Web Administrator

Reston, VA · On-site +1

$85K/yr

... improvements, chatbot content, search tuning, and knowledge base updates. * Support content ... Experience writing SOPs, user guides, training materials, FAQs, or knowledge base articles.

Web Administrator

Reston, VA · On-site

$85K/yr

... improvements, chatbot content, search tuning, and knowledge base updates. * Support content ... Experience writing SOPs, user guides, training materials, FAQs, or knowledge base articles.

Web Administrator

Reston, VA · On-site +1

$85K/yr

... improvements, chatbot content, search tuning, and knowledge base updates. * Support content ... Experience writing SOPs, user guides, training materials, FAQs, or knowledge base articles.

... improvements, chatbot content, search tuning, and knowledge base updates. * Support content ... Experience writing SOPs, user guides, training materials, FAQs, or knowledge base articles.

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Showing results 1-20

Chatbot Training information

What are the key skills and qualifications needed to thrive as a Chatbot Trainer, and why are they important?

To thrive as a Chatbot Trainer, you need a strong understanding of natural language processing (NLP), data annotation, and linguistic analysis, typically supported by a background in linguistics, computer science, or a related field. Familiarity with annotation tools, training platforms like Dialogflow or Rasa, and knowledge of data labeling standards and processes is essential. Attention to detail, critical thinking, and clear communication are important soft skills for effective data labeling and iterative improvement. These skills ensure that chatbots are trained accurately and efficiently, leading to better conversational AI performance and user satisfaction.

What is chatbot training?

Chatbot training is the process of teaching a chatbot how to understand and respond to user inputs effectively. This involves feeding the chatbot with example conversations, questions, and answers so it can learn to interpret language, context, and intent. Training can be done using rule-based approaches, machine learning, or a combination of both. The goal is to improve the chatbot’s accuracy and ability to provide helpful, human-like responses.

What is the difference between Chatbot Training vs Chatbot Developer?

AspectChatbot TrainingChatbot Developer
Required SkillsNatural Language Processing, data annotation, machine learning basicsProgramming, software development, API integration
Work EnvironmentData labeling, model refinement, content creationCoding, system design, deployment
CertificationsAI/ML certifications, NLP coursesSoftware development certifications, coding bootcamps
Industry UsageTraining AI models for chatbots, improving understandingBuilding and maintaining chatbot platforms and applications

Chatbot Training focuses on preparing AI models through data annotation and refining language understanding, while Chatbot Developers build and implement the chatbot systems using programming skills. Both roles are essential in creating effective chatbots but differ in technical complexity and daily tasks.

What are some common challenges faced by professionals working in chatbot training, and how can they address them?

Professionals in chatbot training often encounter challenges such as ensuring the chatbot understands various user intents, handling ambiguous language, and continuously improving the bot's responses based on user feedback. Collaborating closely with data scientists, developers, and UX designers is essential to iteratively refine training data and conversational flows. Staying updated with advancements in natural language processing (NLP) can also help address limitations and maintain a high-quality user experience. Regular review of chat logs and user interactions is key to identifying areas for improvement.
What cities in Virginia are hiring for Chatbot Training jobs? Cities in Virginia with the most Chatbot Training job openings:
Infographic showing various Chatbot Training job openings in Virginia as of July 2026, with employment types broken down into 2% Locum Tenens, 61% As Needed, 2% Full Time, 1% Part Time, 32% Nights, and 2% Summer. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.
Senior Director, Software Engineering

Senior Director, Software Engineering

Freddie Mac

Mclean, VA

$255K/yr

Full-time

Posted 6 days ago


Job description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it's at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

Position Overview:

Freddie Mac is seeking a Sr. Director, Generative AI Development to lead a team of engineers building and operating internal Generative AI capabilities, including the company's internal chatbot and additional Gen AI-enabled products. This leader will drive delivery excellence, engineering rigor, and secure-by-design implementation across the full software lifecycle-partnering closely with Product, Architecture, Cybersecurity, Data, Model Risk, Legal/Compliance, and business stakeholders.

Your Impact:
  • Lead, coach, and grow a high-performing GenAI engineering team; set clear expectations, career paths, and performance standards.

  • Own delivery for internal AI chatbot and GenAI services: roadmap execution, sprint planning, dependency management, and release readiness.

  • Establish engineering standards for GenAI applications: prompt/service design patterns, evaluation frameworks, observability, and incident response.

  • Drive architecture and implementation for LLM-enabled systems (e.g., RAG, tool/function calling, agentic workflows) aligned to enterprise standards.

  • Ensure security, privacy, and compliance requirements are built-in (e.g., data handling, access controls, auditability, retention).

  • Partner with Model Risk Management and governance stakeholders to support appropriate documentation, testing, and controls for GenAI solutions.

  • Implement and monitor quality metrics (latency, cost per interaction, groundedness, hallucination rate, user satisfaction) and continuously improve.

  • Manage vendor/platform dependencies (LLM providers, orchestration frameworks, vector stores) and guide build-vs-buy decisions.

  • Communicate status, risks, and tradeoffs to senior technology and business leaders; translate business needs into engineering plans.

Qualifications:
  • 12+ years of software engineering experience, including 5+ years leading engineering teams/managers.

  • Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).

  • Proven experience delivering production-grade AI/ML or GenAI-enabled applications at enterprise scale.

  • Strong knowledge of modern cloud-native engineering (APIs, microservices, containers, CI/CD, IaC).

  • Recent hands-on coding experience.

  • Experience with secure software development practices and enterprise risk/compliance expectations.

  • Strong stakeholder management skills; ability to influence across product, security, and governance functions.

Preferred Qualifications:

  • Experience implementing RAG with vector databases and enterprise search.

  • Familiarity with LLM evaluation methods and automated testing approaches for GenAI.

  • Experience with MLOps/LLMOps, model monitoring, and cost optimization.

  • Background in regulated industries (financial services, mortgage, insurance) and related control environments.

Keys to Success in this Role:

  • Stable, measurable internal AI chatbot platform with strong adoption and clear quality/cost metrics.

  • Repeatable engineering patterns for GenAI features (RAG, tools, evaluation, guardrails) used across projects.

  • Improved delivery predictability and engineering quality (test coverage, incident reduction, faster release cycles).

  • Strong partnership model with Cybersecurity, Architecture, and Model Risk to accelerate safe delivery.

Current Freddie Mac employees please apply through the internal career site.

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac's business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.

Time-type:Full timeFLSA Status:Exempt

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $228,000 - $342,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.Employment Type: FULL_TIME

Freddie Mac logo

About Freddie Mac

Sourced by ZipRecruiter

Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others.

Industry

Finance and insurance

Company size

5,001 - 10,000 Employees

Headquarters location

McLean, VA, US

Year founded

1970