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Applications Engineer Remote Jobs in Virginia (NOW HIRING)

ARSIEM

Applications Developer III

Arlington, VA · Remote

ARSIEM is looking for an Applications Developer to design, troubleshoot, and implement software ... Must be able to work collaboratively across remote and physical locations Preferred Qualifications

ARSIEM

Applications Developer III

Arlington, VA · On-site +1

ARSIEM is looking for an Applications Developer to design, troubleshoot, and implement software ... Must be able to work collaboratively across remote and physical locations Preferred Qualifications

ARSIEM

Applications Developer II

Arlington, VA · On-site +1

ARSIEM is looking for an Applications Developer to design, troubleshoot, and implement software ... Must be able to work collaboratively across remote and physical locations Preferred Qualifications

ARSIEM

Applications Developer II

Arlington, VA · On-site +1

ARSIEM is looking for an Applications Developer to design, troubleshoot, and implement software ... Must be able to work collaboratively across remote and physical locations Preferred Qualifications

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

LLMs (Large Language Models), RAGs, and AI agent systems for various business applications ... Engineer high-quality features and maintain training/inference pipelines. Cloud and Platform ...

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Applications Engineer Remote information

What does an applications engineer do when working remotely?

A remote Applications Engineer designs, develops, and supports software or hardware solutions tailored to customer needs, all from a remote location. They collaborate with clients, sales teams, and development teams through virtual meetings and digital tools to ensure products are integrated and optimized for specific applications. Their responsibilities often include troubleshooting technical issues, providing product demonstrations, and assisting with implementation and customization. Working remotely allows them to serve clients across various regions while maintaining effective communication and support.

What are the key skills and qualifications needed to thrive as an applications engineer remote?

To thrive as a remote Applications Engineer, you need a solid background in engineering principles, programming, and problem-solving, often supported by a degree in engineering or computer science. Familiarity with CAD software, simulation tools, and customer relationship management (CRM) systems is typically required, along with relevant certifications. Excellent communication, self-motivation, and time management are standout soft skills, especially in a remote setting. These skills and qualities are crucial to effectively deliver technical solutions, support clients, and collaborate with teams across different locations.

What is the difference between Applications Engineer Remote vs Applications Engineer on-site?

AspectApplications Engineer RemoteApplications Engineer on-site
Work EnvironmentPerforms duties remotely, often from home, with virtual collaborationWorks at a company location, interacting face-to-face with teams and clients
Required CredentialsTypically requires engineering degree and technical certifications, similar to on-site rolesSame credentials as remote roles, with emphasis on communication skills for in-person interactions
Industry UsageCommon in tech, software, and engineering firms offering remote optionsTraditional in manufacturing, hardware, and engineering industries
Work FlexibilityHigh flexibility in location and schedule, depending on employer policiesLess flexible, with fixed working hours and location

Applications Engineer Remote and on-site roles share similar technical requirements and industry usage. The main difference lies in the work environment and flexibility, with remote positions offering greater location independence while on-site roles involve physical presence at the workplace.

How does an applications engineer remote typically collaborate with product development and customer support teams?

As a remote Applications Engineer, collaboration with product development and customer support is often achieved through regular virtual meetings, shared project management platforms, and real-time communication tools. You'll frequently translate customer requirements into technical solutions, working closely with development teams to relay feedback and troubleshoot issues. Proactive communication and clear documentation are essential for successful cross-functional teamwork in a remote setting. This structure allows you to contribute meaningfully to product improvements while maintaining strong relationships with both internal teams and clients.
What are the most commonly searched types of Applications Engineer jobs in Virginia? The most popular types of Applications Engineer jobs in Virginia are:
What are popular job titles related to Applications Engineer Remote jobs in Virginia? For Applications Engineer Remote jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Applications Engineer Remote jobs in Virginia look for? The top searched job categories for Applications Engineer Remote jobs in Virginia are:
What cities in Virginia are hiring for Applications Engineer Remote jobs? Cities in Virginia with the most Applications Engineer Remote job openings:
Applications Engineer Remote jobs near you

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 today. 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

491st 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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