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Remote Solutions Engineer Jobs in Hampton, VA (NOW HIRING)

Booz Allen Hamilton, Inc.

Palantir Data Engineer

Norfolk, VA · On-site +1

$61K - $141K/yr

Remote Work: Hybrid Job Number: R0244009 Location: Norfolk,VA,US Share job via: Share Palantir Data ... Experience with mission analytics or government-focused data solutions * Experience with AI or ML ...

ASEC

Network Engineer

Virginia Beach, VA · On-site +1

$135K - $150K/yr

The Network Engineer will be part of a team responsible for the design, implementation, security ... remote training participants. * Implement boundary defense solutions and network segmentation.

SAIC

Systems Engineer

Hampton, VA · Remote

$80K - $120K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is looking for a Data Integrity ... Review, analyze and recommend solutions with regard to Government requirements and design ...

Commence

Full Stack Software Engineer

Virginia Beach, VA · Remote

$105K - $135K/yr

We combine quality data-driven solutions that fuel answers, technology that advances performance ... This is a remote position. Candidates must be able to sit, read, work on a computer, and watch a ...

Commence

Sr Site Reliability Engineer

Virginia Beach, VA · On-site +1

$145K - $175K/yr

We combine quality data-driven solutions that fuel answers, technology that advances performance ... This is a remote position. While performing the duties of this job, the employee regularly works in ...

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Remote Solutions Engineer information

See Hampton, VA salary details

$43K

$119.1K

$175.4K

How much do remote solutions engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote solutions engineer in Hampton, VA is $119,146.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,100.00 and $135,800.00 per year, depending on experience, location, and employer.

What is a remote solutions engineer?

A Remote Solutions Engineer is a technical professional who helps customers understand, implement, and optimize a company's products or services, typically in a pre-sales or post-sales capacity. They work remotely to assess client needs, provide technical demonstrations, troubleshoot issues, and collaborate with sales and engineering teams. Their role often requires a mix of technical expertise, communication skills, and problem-solving abilities to ensure customer success.

What are the primary responsibilities of a remote solutions engineer on a daily basis?

A Remote Solutions Engineer typically spends their days designing technical solutions, troubleshooting client issues, and collaborating with both internal teams and clients via video calls, chat, or emails. Responsibilities often include gathering requirements, developing and implementing architectures, supporting technical pre-sales processes, and providing ongoing support and optimization for deployed solutions. Because the role is remote, strong self-management and proactive communication are essential, and most interaction happens in a virtual team environment. This allows for flexibility, but also requires a high degree of autonomy and accountability to ensure project milestones and customer satisfaction are consistently achieved.

What are the key skills and qualifications needed to thrive in the remote solutions engineer position, and why are they important?

To thrive as a Remote Solutions Engineer, you need strong technical expertise in IT systems, software development, and solutions architecture, typically backed by a degree in computer science or a related field. Experience with cloud platforms (like AWS, Azure, or Google Cloud), networking tools, and relevant certifications such as AWS Certified Solutions Architect or CompTIA Network+ are highly valued. Exceptional communication, problem-solving skills, and the ability to manage projects independently are crucial soft skills for this remote role. These competencies ensure you can effectively design, implement, and support tailored solutions for clients while collaborating with distributed teams and meeting business objectives.

What are popular job titles related to Remote Solutions Engineer jobs in Hampton, VA?

For Remote Solutions Engineer jobs in Hampton, VA, the most frequently searched job titles are:

What job categories do people searching Remote Solutions Engineer jobs in Hampton, VA look for?

The top searched job categories for Remote Solutions Engineer jobs in Hampton, VA are:

What cities near Hampton, VA are hiring for Remote Solutions Engineer jobs?

Cities near Hampton, VA with the most Remote Solutions Engineer job openings:

Remote Solutions Engineer jobs near you
Infographic showing various Remote Solutions Engineer job openings in Hampton, VA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $119,146 per year, or $57.3 per hour.

Senior MLOps & Generative AI Engineer - Remote

Sentara Healthcare

Virginia Beach, VA • On-site, Remote

$99K - $136K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago

Sentara Health rating

6.7

Company rating: 6.7 out of 10

Based on 412 frontline employees who took The Breakroom Quiz

530th of 891 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!
Selected candidates would be required to be onsite for final round of team interview
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
• Pet Insurance
• Legal Resources Plan
• Colleagues have the opportunity to earn an annual discretionary bonus if established 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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