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Virtual Assistant Engineer Jobs in Washington (NOW HIRING)

They are seeking a Network Engineer to assist with monitoring IT systems, coordinating engineering ... virtual infrastructure domain • Maintain up to date network topology drawings. • Perform ...

DevOps Engineer

Hanover, MD

$52.50 - $72/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Monitor, maintain, install, and support networked virtual machines, containers and software applications * Assist software developers, integration, and test engineers to best utilize DevOps ...

DevOps Engineer

Hanover, MD · On-site

$52.50 - $72/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Monitor, maintain, install, and support networked virtual machines, containers and software applications * Assist software developers, integration, and test engineers to best utilize DevOps ...

DevOps Engineer

Hanover, MD · On-site

$115K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Monitor, maintain, install, and support networked virtual machines, containers and software applications * Assist software developers, integration, and test engineers to best utilize DevOps ...

DevOps Engineer

Hanover, MD · On-site

$115K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Monitor, maintain, install, and support networked virtual machines, containers and software applications * Assist software developers, integration, and test engineers to best utilize DevOps ...

DevOps Engineer

Hanover, MD

$52.50 - $72/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Monitor, maintain, install, and support networked virtual machines, containers and software applications * Assist software developers, integration, and test engineers to best utilize DevOps ...

Cloud Engineer (Junior)

Hyattsville, MD · On-site +1

$56 - $74.75/hr

Responsibilities - Junior Cloud Engineering, Infrastructure & Automation * Assist with the design ... Understanding of cloud computing concepts including virtual machines, storage, networking ...

New

Cloud Engineer (Junior)

Hyattsville, MD · On-site

$56 - $74.75/hr

Responsibilities - Junior Cloud Engineering, Infrastructure & Automation * Assist with the design ... Understanding of cloud computing concepts including virtual machines, storage, networking ...

New

DevOps Engineer

Hanover, MD · On-site

$52 - $71.25/hr

... virtual machines, containers and software applications • Assist software developers, integration, and test engineers to best utilize DevOps capabilities • Trouble-shoot capabilities to diagnose ...

Showing results 21-40

Virtual Assistant Engineer information

What is the difference between Virtual Assistant Engineer vs Virtual Assistant?

AspectVirtual Assistant EngineerVirtual Assistant
Required CredentialsTechnical certifications, programming knowledgeBasic computer skills, communication skills
Work EnvironmentRemote, technical projects, client-specific tasksRemote, administrative, scheduling, customer support
Employer & Industry UsageTech companies, startups, IT service providersSmall businesses, entrepreneurs, online service providers
Common Search & Comparison IntentTechnical skills, engineering tasks, software developmentAdministrative support, scheduling, general assistance

The main difference between a Virtual Assistant Engineer and a Virtual Assistant lies in their skill sets and work focus. Virtual Assistant Engineers typically have technical certifications and work on software development or engineering projects, while Virtual Assistants handle administrative and support tasks. Both roles are remote and serve different industry needs, with the Engineer role requiring more technical expertise.

How does a virtual assistant engineer typically collaborate with cross-functional teams to improve virtual assistant performance?

Virtual Assistant Engineers regularly work with product managers, UX designers, and data scientists to enhance the capabilities and user experience of virtual assistants. Collaboration often involves participating in sprint meetings, sharing data insights, and integrating user feedback into system improvements. This teamwork ensures the virtual assistant remains accurate, responsive, and aligned with evolving business needs. Effective communication and openness to iterative feedback are essential for success in this collaborative environment.

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

To thrive as a Virtual Assistant Engineer, you need strong programming skills (often in Python, Java, or C#), experience with AI and NLP technologies, and a degree in computer science or a related field. Familiarity with platforms like Amazon Alexa, Google Assistant, dialog management systems, and cloud-based development environments is typically required. Excellent problem-solving, communication, and teamwork abilities help you collaborate effectively and design user-friendly voice or chat interfaces. These skills ensure you can build, deploy, and refine intelligent virtual assistants that enhance user experiences and meet business objectives.

What is a virtual assistant engineer?

Virtual Assistant Engineers are professionals who design, develop, and maintain virtual assistant technologies, such as chatbots and voice-activated AI systems. They work with artificial intelligence, natural language processing, and machine learning tools to create digital assistants that understand and respond to user input. Their responsibilities may include coding backend logic, integrating APIs, and continually improving the assistant's performance based on user interactions. Virtual Assistant Engineers often collaborate with UX designers, data scientists, and product managers to deliver seamless user experiences.

What are popular job titles related to Virtual Assistant Engineer jobs in Washington?

For Virtual Assistant Engineer jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Virtual Assistant Engineer jobs in Washington look for?

The top searched job categories for Virtual Assistant Engineer jobs in Washington are:

Modeling, Analysis & Simulation (MA&S) Engineer

Peraton

Herndon, VA • On-site

$135K - $216K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

50th of 223 rated it services


Job description

Responsibilities
Peraton is seeking an experienced Modeling, Analysis & Simulation (MA&S) Engineer to lead the development and application of models, simulations, and analytical frameworks that support the engineering, integration, and validation of complex BNATCS systems. In Peraton's role as a systems integrator, this position is essential to understanding how independently developed components will behave when brought together, long before physical integration occurs.
This role sits at the intersection of model-based systems engineering (MBSE), simulation science, and artificial intelligence - applying AI-augmented modeling techniques to accelerate system design, predict emergent behaviors, automate trade-off analyses, and enhance the fidelity and efficiency of simulation environments. You will define the MA&S strategy, build and govern the modeling ecosystem, and guide engineering teams in using models as the authoritative source of truth for design decisions, integration verification, and performance analysis across the enterprise.
This role is based in Herndon, VA.
Key Responsibilities
  • Define and maintain the enterprise MA&S strategy and architecture, establishing how models, simulations, and analytical tools are developed, governed, and reused across the integrated program
  • Lead model-based systems engineering (MBSE) initiatives using industry-standard tools and languages (Cameo, Sparx EA, MATLAB/Simulink, SysML, UAF) to create authoritative system models that drive requirements, design, integration, and verification activities
  • Develop and maintain system-of-systems models that represent the integrated behavior of multi-vendor components, capturing interfaces, dependencies, data flows, and emergent properties across technical and organizational boundaries
  • Establish model governance standards - configuration management, version control, validation criteria, and model pedigree tracking - to ensure model trustworthiness across teams and subcontractors
  • Apply AI and machine learning techniques to enhance MBSE workflows - including automated model generation from requirements, natural language processing (NLP) for requirements analysis, and AI-assisted consistency and completeness checking across large model repositories
  • Develop and deploy AI-driven surrogate models and digital twins that approximate high-fidelity simulations at reduced computational cost, enabling rapid design space exploration and real-time decision support
  • Leverage generative AI and large language models (LLMs) to accelerate model documentation, translate between modeling formalisms, and assist engineers in querying and navigating complex system models
  • Implement machine learning-based predictive analytics to identify integration risks, performance bottlenecks, and failure modes from historical simulation data and system telemetry
  • Evaluate and integrate emerging AI-for-engineering tools into the MA&S toolchain, assessing their maturity, trustworthiness, and applicability to safety-critical and mission-critical modeling contexts
  • Design and operate simulation environments - constructive, virtual, and hardware-in-the-loop - that replicate integrated system behavior for performance analysis, stress testing, and scenario exploration
  • Conduct trade-off analyses, sensitivity studies, and Monte Carlo simulations to quantify risk, evaluate design alternatives, and support engineering decision-making
  • Develop integration simulation frameworks that allow multi-vendor components to be tested in a virtual integration environment prior to physical integration, reducing risk and accelerating delivery
  • Perform performance modeling and capacity analysis for real-time, low-latency, and high-availability systems, ensuring that integrated solutions meet stringent operational requirements
  • Support verification and validation (V&V) activities by providing model-based evidence, simulation results, and analytical artifacts that demonstrate system compliance with requirements
  • Collaborate with enterprise architects, software architects, cybersecurity teams, and data architects to ensure models and simulations are aligned with broader architectural governance and design decisions
  • Conduct technical reviews of vendor and subcontractor modeling deliverables to ensure alignment with enterprise MBSE standards, interface specifications, and model quality requirements
  • Define and manage model exchange standards and interfaces across the integrated program, enabling interoperability between modeling tools used by different teams and subcontractors
  • Translate complex modeling results, simulation outcomes, and AI-driven insights into clear, actionable guidance for program leadership, government stakeholders, and non-technical audiences
  • Mentor and guide systems engineers, simulation developers, and data scientists in MBSE practices, simulation techniques, and the responsible application of AI in engineering workflows

#BNATC
#LSI2
Qualifications
Required Qualifications
  • Public Trust Clearance - Ability to Obtain and Maintain
  • 15+ years of experience in modeling and simulation, systems engineering, or MBSE within large-scale programs
  • Bachelor's degree in Systems Engineering, Computer Science, Aerospace Engineering, Mathematics, Physics, or a related field (or 4 additional years of relevant experience in lieu of degree)
  • Demonstrated experience serving as an MA&S lead within a systems integrator environment, developing models and simulations that validate multi-vendor, multi-technology integrated solutions
  • Deep expertise in model-based systems engineering (MBSE) using SysML, UAF, or equivalent modeling languages and tools (Cameo, Sparx EA, MATLAB/Simulink, Rhapsody)
  • Proven experience applying AI and machine learning techniques to engineering modeling workflows - surrogate modeling, automated analysis, NLP-based requirements processing, or predictive analytics
  • Strong command of simulation methodologies - discrete event simulation, agent-based modeling, Monte Carlo analysis, hardware-in-the-loop, and constructive simulation environments
  • Hands-on experience with simulation frameworks and tools (AnyLogic, Arena, AFSIM, STK, custom simulation engines, or equivalent)
  • Proficiency in Python, MATLAB, Java, or other languages commonly used in modeling, simulation, and AI/ML development
  • Solid understanding of systems engineering lifecycle processes - requirements analysis, architecture design, integration, verification, and validation - and how models support each phase
  • Working knowledge of federal frameworks (NIST, FedRAMP, RMF) as they relate to the security and accreditation of modeling and simulation environments
  • Experience supporting federal or DoD programs with complex integration and system-of-systems challenges
  • Background in mission-critical or safety-critical systems where model accuracy and simulation fidelity directly impact operational and safety outcomes
  • Proven ability to lead cross-functional teams and drive alignment across systems engineering, software development, test, and operations disciplines

Preferred Qualifications
  • Experience with modeling and simulation for aviation, air traffic management, or national airspace systems
  • Background in digital twin development - creating persistent, data-connected virtual representations of physical systems for ongoing monitoring and analysis
  • Familiarity with real-time simulation, low-latency modeling, and edge computing for simulation deployment
  • Experience with cloud-based simulation environments (AWS, Azure) including high-performance computing (HPC), containerized simulation workloads, and scalable compute for large-scale Monte Carlo or parametric studies
  • Knowledge of data architecture and data integration as it relates to feeding operational data into models and simulations for calibration and validation
  • ITIL certification and experience aligning MA&S activities with ITSM and configuration management processes
  • Experience with AIOps, observability platforms, and using operational telemetry to continuously refine and validate models
  • Familiarity with AI governance, model explainability, and trustworthy AI frameworks as applied to engineering decision support
  • Relevant certifications such as INCOSE CSEP/ESEP, AWS Solutions Architect, or certifications in AI/ML (e.g., AWS Machine Learning Specialty, Google Professional ML Engineer)

#BNATCS #LSI
Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.
Target Salary Range
$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017