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Remote New Grad Software Engineer Jobs in Chesapeake, VA

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 ... The candidate must be able to effectively interface with software developers and have a good ...

EffOne Technologies

Be Seen First

Senior Quickbase Developer

Virginia Beach, VA · Remote

$46 - $50/hr

The ideal candidate will possess a strong foundation in software development, system design, and ... It is a 6+ months contract and a remote position. Duties Collaborate with cross-functional teams to ...

New

Varsity Tutors

Software Tutor

Norfolk, VA · Remote

$18 - $40/hr

Deep knowledge of software development methodologies, programming languages, version control ... Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West ...

Varsity Tutors

Software Tutor

Virginia Beach, VA · Remote

$18 - $40/hr

Deep knowledge of software development methodologies, programming languages, version control ... Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West ...

Quora

iOS Engineer -Remote

Norfolk, VA · Remote

$166K - $191K/yr

Build new user-facing features and help drive the Poe product roadmap * Create tools and ... Own the entire software development process from timeline estimation to coding, testing and release ...

Quora

iOS Engineer -Remote

Virginia Beach, VA · Remote

$166K - $191K/yr

Build new user-facing features and help drive the Poe product roadmap * Create tools and ... Own the entire software development process from timeline estimation to coding, testing and release ...

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Showing results 21-40

All JobsNew Grad Software Engineer JobsRemote New Grad Software Engineer JobsRemote New Grad Software Engineer Jobs in Chesapeake, VA

Remote New Grad Software Engineer information

See Chesapeake, VA salary details

$61.7K

$143.3K

$199.6K

How much do remote new grad software engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for remote new grad software engineer in Chesapeake, VA is $143,273.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $168,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote New Grad Software Engineer vs Remote Software Developer?

AspectRemote New Grad Software EngineerRemote Software Developer
Required CredentialsBachelor's degree in CS or related field, internship experience often preferredSimilar educational background, may require more professional experience
Work EnvironmentEntry-level, mentored, collaborative teams, often in tech companies or startupsCan be entry or mid-level, more autonomous, in various industries
Employer & Industry UsageCommon in tech, startups, large corporations hiring entry-level talentUsed across industries, including tech, finance, healthcare, often for experienced roles

The main difference is that a Remote New Grad Software Engineer is an entry-level role designed for recent graduates, focusing on learning and growth, while a Remote Software Developer may have more experience and responsibilities. Both roles often require similar educational backgrounds and work in similar environments, but the developer role can involve more independent work and complex projects.

What are some unique challenges new grad software engineers face when starting in a fully remote environment?

New grad software engineers working remotely often encounter challenges such as building strong relationships with teammates, navigating company culture, and getting timely feedback. Without in-person interactions, it can take extra effort to communicate effectively, ask questions, and stay connected with mentors. Proactively reaching out through messaging tools, participating in virtual meetings, and setting up regular check-ins with managers can help ease the transition and ensure continued growth and support.

What is a remote new grad software engineer?

A Remote New Grad Software Engineer is an entry-level professional who has recently graduated from college or university with a degree in computer science or a related field and works from a location outside the traditional office setting. These engineers are responsible for designing, developing, testing, and maintaining software applications while collaborating with their teams virtually. Remote positions offer flexibility and the opportunity to work with companies regardless of geographic location, but they also require strong communication skills and self-motivation.

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

To thrive as a Remote New Grad Software Engineer, you need a solid understanding of programming languages (such as Python, Java, or JavaScript), algorithms, and software development principles, usually supported by a relevant degree or coding bootcamp experience. Familiarity with version control systems like Git, collaborative tools (e.g., Jira, Slack), and cloud platforms is typically expected. Strong self-motivation, effective communication, and the ability to learn independently are vital soft skills in a remote environment. These competencies ensure you can contribute to codebases, collaborate across distances, and adapt quickly to evolving technical challenges.

What are popular job titles related to Remote New Grad Software Engineer jobs in Chesapeake, VA?

For Remote New Grad Software Engineer jobs in Chesapeake, VA, the most frequently searched job titles are:

What job categories do people searching Remote New Grad Software Engineer jobs in Chesapeake, VA look for?

The top searched job categories for Remote New Grad Software Engineer jobs in Chesapeake, VA are:

What cities near Chesapeake, VA are hiring for Remote New Grad Software Engineer jobs?

Cities near Chesapeake, VA with the most Remote New Grad Software Engineer job openings:

Remote New Grad Software Engineer 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 1 day ago. Applications are no longer accepted.

Sentara Health rating

6.8

Company rating: 6.8 out of 10

Based on 411 frontline employees who took The Breakroom Quiz

494th 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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