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Remote Automation Engineer Jobs in Chesapeake, VA

Commence

Sr Site Reliability Engineer

Virginia Beach, VA · On-site +1

$145K - $175K/yr

Reduce operational toil through automation; eliminate manual processes before they become habits ... This is a remote position. While performing the duties of this job, the employee regularly works in ...

Commence

Sr Site Reliability Engineer

Virginia Beach, VA · On-site +1

$175K/yr

Reduce operational toil through automation; eliminate manual processes before they become habits ... This is a remote position. While performing the duties of this job, the employee regularly works in ...

Booz Allen Hamilton, Inc.

Network Engineer

Norfolk, VA · On-site +1

$52K - $108K/yr

Remote Work: Hybrid Job Number: R0246197 Location: Norfolk,VA,US Share job via: Share Network ... Knowledge of scripting or automation tools such as Python or Ansible * Knowledge of cloud ...

Booz Allen Hamilton, Inc.

Network Engineer

Norfolk, VA · On-site +1

$61K - $141K/yr

Remote Work: Hybrid Job Number: R0243281 Location: Norfolk,VA,US Share job via: Share Network ... Knowledge of scripting or automation tools such as Python or Ansible * Knowledge of cloud ...

ManTech

Senior Database Administrator

Virginia Beach, VA · Remote

$94K - $157K/yr

Automation & Infrastructure: Build and manage database infrastructure using Infrastructure-as-Code ... Work with developers, DevOps, and data scientists to design efficient, scalable, and secure data ...

Aggreko

Junior Regional Controls Associate

Norfolk, VA · Remote

From world-class events that last a few weeks to mining operations and remote communities who rely ... Identify and implement opportunities to enhance efficiency, automation and sustainability of the SO ...

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Remote Automation Engineer information

See Chesapeake, VA salary details

$35.9K

$104K

$158.3K

How much do remote automation engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote automation engineer in Chesapeake, VA is $104,040.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $119,900.00 per year, depending on experience, location, and employer.

What is a remote automation engineer?

A Remote Automation Engineer is a professional who designs, develops, and maintains automated systems and processes, often working from a remote location rather than on-site. They typically focus on creating scripts, tools, and workflows that help improve efficiency, quality, and reliability in software development, IT operations, or industrial processes. Their responsibilities may include writing code for test automation, configuring CI/CD pipelines, and collaborating with remote teams to optimize business operations. Working remotely allows them to support projects in various locations while leveraging digital communication and collaboration tools.

What does a remote automation engineer do?

A remote automation engineer uses technology to streamline, improve, and automate the manufacturing process. Your responsibilities in this work from home position include QA duties, testing software, developing computer systems, simulating programs, and using sensors to get accurate measurements. Your duties construct the automation processes of a specific manufacturing process. The different processes you work with govern the delivery and production of the process. You streamline processes for maximum efficiency without violating regulations or sacrificing the quality of products.

What are the key skills and qualifications needed to thrive as a remote automation engineer, and why are they important?

To thrive as a Remote Automation Engineer, you need a solid background in software development, scripting languages (such as Python or JavaScript), and automation frameworks, typically supported by a degree in computer science or a related field. Familiarity with CI/CD pipelines, testing tools like Selenium or Jenkins, and certifications such as ISTQB or AWS Certified DevOps Engineer are often required. Strong problem-solving abilities, self-motivation, and clear communication are critical soft skills for collaborating effectively in a distributed environment. These competencies ensure efficient automation processes, seamless integration, and successful remote teamwork in fast-paced technology projects.

How do remote automation engineers typically collaborate with on-site teams to ensure project success?

Remote Automation Engineers often work closely with on-site teams through regular video meetings, collaborative project management tools, and shared documentation platforms. Clear communication is key, as remote engineers may need to coordinate testing schedules, troubleshoot issues in real-time, and provide virtual support during equipment installation or updates. It's common to use remote desktop software and cloud-based environments to access systems securely. Proactive communication and responsiveness help bridge the distance, ensuring that automation projects stay on track and meet quality standards.

What is the difference between Remote Automation Engineer vs Remote Software Developer?

AspectRemote Automation EngineerRemote Software Developer
Required CredentialsBachelor's in Engineering, certifications in automation tools (e.g., PLC, SCADA)Bachelor's in Computer Science or related, coding certifications (e.g., Java, Python)
Work EnvironmentIndustrial settings, control systems, manufacturingOffice or remote, software development environments
Employer & Industry UsageManufacturing, industrial automation companiesTech companies, startups, software firms
Common Search & ComparisonAutomation, control systems, industrial processesProgramming, app development, coding projects

Remote Automation Engineers focus on designing and maintaining automation systems in industrial environments, requiring engineering credentials and knowledge of control systems. Remote Software Developers primarily write and maintain software applications, with a focus on coding skills and software development tools. While both roles can be remote, their industries, tools, and expertise areas differ significantly.

Are remote automation engineers in demand?

Remote automation engineers are in high demand due to the increasing adoption of automation technologies across industries. They are sought after for their skills in scripting, programming, and working with tools like Python, Jenkins, and Selenium, often requiring certifications and experience with cloud platforms. The role offers opportunities for flexible work arrangements and competitive salaries in the tech sector.

Can remote automation engineers work remotely?

Yes, remote automation engineers can work remotely, as many companies offer flexible work arrangements for this role. The job typically involves using automation tools, scripting, and cloud platforms, which can be managed from any location with internet access. However, some positions may require on-site presence for specific tasks or team collaboration.
More about Remote Automation Engineer jobs

What are the most commonly searched types of Automation Engineer jobs in Chesapeake, VA?

The most popular types of Automation Engineer jobs in Chesapeake, VA are:

What cities near Chesapeake, VA are hiring for Remote Automation Engineer jobs?

Cities near Chesapeake, VA with the most Remote Automation Engineer job openings:

Remote Automation Engineer jobs near you

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 14 days ago

Sentara Health rating

6.7

Company rating: 6.7 out of 10

Based on 412 frontline employees who took The Breakroom Quiz

531st of 888 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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