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Remote Senior Quality Engineer Jobs in Virginia (NOW HIRING)

Ad Hoc

Senior DevOps Engineer

Mclean, VA · Remote

$131K - $168K/yr

Senior DevOps Engineer Job Number: 866 This is a remote position. Ad Hoc is a technology company ... Integrates tools to satisfy non-functional requirements such as quality thresholds, security ...

T-Rex Solutions

Senior DevSecOps Engineer

Arlington, VA · On-site +1

$131K - $180K/yr

This role is primarily remote with potential for occasional meetings at FDIC HQ in Arlington, VA as ... Automated Testing and Quality Engineering * Develop and lead enterprise testing automation ...

T-Rex Solutions

Senior DevSecOps Engineer

Arlington, VA · Remote

$131K - $180K/yr

This role is primarily remote with potential for occasional meetings at FDIC HQ in Arlington, VA as ... Automated Testing and Quality Engineering * Develop and lead enterprise testing automation ...

Ad Hoc

Senior Data Engineer

Mclean, VA · Remote

$107K - $145K/yr

Senior Data Engineer Job Number: 912 This is a remote position. Ad Hoc is a technology company that ... Ensure data quality, integrity, governance, lineage, security, and observability across data ...

Raymond

Senior Civil Engineer

Richmond, VA · On-site +1

Richmond, VA / Remote (Hybrid options available) About Raymond: We are a progressive, forward ... Employee-focused and technology-driven, we deliver high-quality, cost-effective, and precise ...

Ad Hoc

Senior DevOps Engineer

Mclean, VA · Remote

$131K - $168K/yr

Senior DevOps Engineer Job Number: 915 This is a remote position. Ad Hoc is a technology company ... Integrate automated quality gates, security scanning, vulnerability management, and static code ...

Ad Hoc

Senior DevOps Engineer

Mclean, VA · Remote

$131K - $168K/yr

Senior DevOps Engineer Job Number: 910 This is a remote position. Ad Hoc is a technology company ... Integrates tools to satisfy non-functional requirements such as quality thresholds, security ...

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All JobsQuality Engineer JobsRemote Senior Quality Engineer JobsRemote Senior Quality Engineer Jobs in Virginia

Remote Senior Quality Engineer information

What is the difference between Remote Senior Quality Engineer vs Remote Quality Analyst?

AspectRemote Senior Quality EngineerRemote Quality Analyst
CredentialsBachelor's in Engineering, Quality Management certifications (e.g., CQE)Bachelor's in related fields, QA certifications (e.g., ISTQB)
Work EnvironmentDesigning testing strategies, leading QA teams, collaborating with development teamsExecuting test cases, analyzing results, reporting defects
Industry UsageSoftware, manufacturing, tech companiesSoftware, IT services, product companies
Search/Comparison IntentUnderstanding senior QA roles, career progressionEntry to mid-level QA testing roles

The Remote Senior Quality Engineer typically leads testing efforts, designs quality strategies, and collaborates with development teams, requiring more experience and certifications. In contrast, a Remote Quality Analyst focuses on executing tests and reporting issues, often at an entry or mid-level. Both roles are vital in ensuring product quality but differ in responsibilities and seniority.

What does a remote senior quality engineer do?

A Remote Senior Quality Engineer is responsible for ensuring the quality and reliability of software products by designing and implementing test strategies, identifying and troubleshooting defects, and collaborating closely with development teams. They often lead quality assurance (QA) initiatives, mentor junior engineers, and help define best practices for testing in a remote work environment. Their work includes both manual and automated testing, as well as creating and maintaining testing frameworks to ensure products meet high standards before release.

How does a remote senior quality engineer typically collaborate with cross-functional teams to ensure product quality?

As a Remote Senior Quality Engineer, you will regularly work with developers, product managers, and operations teams through virtual meetings, shared documentation, and collaboration tools. You are often responsible for leading test planning sessions, reviewing requirements, and providing feedback to ensure quality is considered early in the development cycle. Effective communication and proactive coordination are key, as you may need to bridge time zones and cultural differences to align quality standards. Utilizing project management and automation platforms is common to streamline workflows and maintain transparency across distributed teams.

What are the key skills and qualifications needed to thrive as a remote senior quality engineer?

To thrive as a Remote Senior Quality Engineer, you need deep expertise in software quality assurance, test automation, and a strong understanding of programming concepts, commonly supported by a degree in computer science or related field. Familiarity with tools such as Selenium, Jenkins, Jira, and CI/CD systems, along with certifications like ISTQB, are typically required. Strong analytical thinking, self-motivation, and effective remote communication skills set outstanding candidates apart. These abilities ensure efficient collaboration, high product quality, and successful delivery within distributed engineering teams.
What are popular job titles related to Remote Senior Quality Engineer jobs in Virginia? For Remote Senior Quality Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Senior Quality Engineer jobs in Virginia look for? The top searched job categories for Remote Senior Quality Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Senior Quality Engineer jobs? Cities in Virginia with the most Remote Senior Quality Engineer job openings:
Remote Senior Quality Engineer jobs near you
Infographic showing various Remote Senior Quality Engineer job openings in Virginia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Senior MLOps & Generative AI Engineer - Remote

Sentara Health

Virginia Beach, VA • Remote

$90K - $123K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Sentara Health rating

6.8

Company rating: 6.8 out of 10

Based on 398 frontline employees who took The Breakroom Quiz

493rd of 887 rated healthcare providers

Job description

City/State Virginia Beach, VA Work Shift Multiple shifts available Overview: Sentara is hiring a Senior MLOps & Generative AI Engineer! This position is fully remote! Candidates must reside in one of the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming. Overview We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence. This role combines two critical focus areas:
  • MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities.
  • Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.
As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments. Key Responsibilities MLOps Engineering Responsibilities
  • Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
  • Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
  • Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
  • Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
  • Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
  • Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
  • Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
  • Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code.
  • Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them.
  • Support enterprise AI governance, compliance, auditability, and model risk management requirements.
  • Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems.
Generative AI Engineering Responsibilities
  • Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
  • Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
  • Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability.
  • Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases.
  • Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics.
  • Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
  • Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications.
  • Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
  • Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
  • Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement.
  • Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives.
  • Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
  • Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices.
Required Qualifications
  • 5+ years of experience building and deploying production software, ML systems, or AI platforms.
  • 1+ years of hands-on experience building production Generative AI or LLM-based applications.
  • Strong programming skills in Python and experience with software engineering best practices.
  • Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent.
  • Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
  • Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
  • Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
  • Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
  • Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
  • Experience building monitoring, observability, and alerting solutions for ML and AI systems.
  • Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
  • Experience designing secure, scalable, production-ready AI platforms and services.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.
Preferred Qualifications
  • Previous experience implementing Generative AI and MLOps solutions within healthcare environments.
  • Experience working with EPIC or healthcare interoperability platforms.
  • Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices.
  • Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
  • Experience with GPU infrastructure optimization and scalable inference architectures.
  • Familiarity with multi-agent AI systems and autonomous workflows.
  • Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
  • Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
  • Experience with enterprise AI platform architecture and internal developer platforms.
  • Prior experience mentoring engineers and leading technical initiatives.
Education
  • 5+ years of relevant experience with a degree (Required)
or
  • 7+ years of relevant experience without a degree (Required)
  • Experience in lieu of Bachelor's Degree.
Certification/Licensure
  • No specific certification or licensure requirements
Experience
  • 5 to 7 years of relevant experience
We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Keywords: Talroo-IT, MLOps, Gen AI, LLM, AWS, Azure, GCP, AI/ML, Python, PyTorch, Hugging Face Transformers, TensorFlow, RAG, EPIC, HIPAA, AI Governance Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

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