Technical Architect Jobs in Virginia
Technical Architect jobs in Virginia are among the most actively recruited in the mid-Atlantic region, concentrated in defense IT, federal consulting, and enterprise cloud transformation across seniority levels from associate to principal. The heaviest hiring is in the Northern Virginia corridor, Richmond, and the Hampton Roads area, where employers like Leidos, Booz Allen Hamilton, and SAIC consistently recruit technical architects for large-scale government and commercial programs. In-demand specialties include cloud architecture, cybersecurity-focused infrastructure, and enterprise integration. Find a role that fits below and apply directly.
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hatch I.T. is partnering with Expression to find an AI Architect (Technical Lead). See details below:
About The Role:
Expression is seeking an experienced AI Architect to serve as Technical Lead designing and technically integrating advanced Artificial Intelligence (AI) and Large Language Model (LLM) capabilities supporting the Department of Homeland Security (DHS).
This role will support the development and integration of secure, mission-focused AI agents within the DHS AI environment. The selected candidate will lead the adaptation of multi-agent AI capabilities, including intelligent workflow orchestration, retrieval-augmented generation (RAG), model evaluation, and governed enterprise data integration, to enhance investigative analysis, information retrieval, report generation, and human decision support.
The ideal candidate is a hands-on AI architect and technical leader with extensive experience designing and delivering enterprise AI applications. You are equally comfortable defining system architecture, developing and reviewing production-quality software, integrating LLMs with enterprise data systems, and mentoring engineers through complex technical challenges.
This position requires a strong understanding of modern AI engineering, distributed application architectures, secure API development, and responsible AI deployment within highly regulated environments. You will work closely with AI engineers, data engineers, program leadership, and Government stakeholders to deliver reliable, explainable, secure, and scalable AI capabilities.
Location and Clearance:
Clearance: Top Secret/SCI required
Location: Shirlington, VA
About the Company:
Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s “Perpetual Innovation” culture focuses on creating immediate and sustainable value for their clients via agile delivery of tailored solutions built through constant engagement with their clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.
Responsibilities:
- Lead the technical architecture, design, and implementation of enterprise AI and agentic AI solutions within the Government's existing AI environment, emphasizing reuse of approved infrastructure, services, and model endpoints.
- Define scalable, secure, and maintainable software architectures integrating LLMs, specialized AI agents, enterprise data services, APIs, and human-in-the-loop workflows.
- Design and implement multi-agent orchestration frameworks, including Responder–Evaluator–Reporter workflows, model selection, prompt management, tool invocation, and structured output validation.
- Lead the integration of Government-approved frontier AI models through authorized endpoints, ensuring appropriate model configuration, version management, performance evaluation, and controlled execution.
- Architect retrieval-augmented generation (RAG) solutions that integrate authorized enterprise data sources while preserving source attribution, access controls, data lineage, and traceability.
- Guide integration with Palantir, Databricks, Elasticsearch, and other approved Government data services through secure APIs and governed interfaces.
- Design secure AI agent execution frameworks incorporating identity propagation, role-based and purpose-based access controls, bounded tool permissions, approval checkpoints, execution limits, and safe failure mechanisms.
- Develop and review production-quality backend services, APIs, and orchestration components using Python and modern software engineering practices.
- Lead architecture and code reviews, resolve complex integration challenges, and establish engineering standards for maintainability, reliability, security, and performance.
- Design evaluation and testing approaches for LLM and multi-agent applications, including factual accuracy, consistency, explainability, latency, scalability, and computational cost.
- Establish observability, logging, prompt and model version tracking, and auditability across AI workflows, ensuring AI-generated outputs can be traced to supporting sources and reviewed by authorized personnel.
- Collaborate with cybersecurity, DevSecOps, privacy, and Government stakeholders to align system designs with approved deployment pipelines, security controls, authorization requirements, and release processes.
- Support the adaptation of existing AI algorithms, prompts, and software components into Government-approved investigative workflows, documenting technical lineage, modifications, and integration requirements.
- Produce solution architecture documents, system design specifications, interface control documents, data-flow diagrams, technical evaluations, and engineering implementation guidance.
- Support technical demonstrations, prototype evaluations, user acceptance activities, and Government design reviews.
- Provide technical leadership and mentorship to AI engineers and data engineers while maintaining meaningful hands-on involvement in architecture, development, debugging, and integration.
- Evaluate proposed third-party AI tools, frameworks, and software components for technical suitability, security implications, integration complexity, and reuse of existing Government capabilities, coordinating recommendations through established approval processes.
Qualifications:
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical field, or equivalent relevant professional experience.
- 12+ years of professional experience in software engineering, AI engineering, data engineering, or enterprise application development, including 3+ years in software architecture or technical leadership roles.
- Demonstrated hands-on experience architecting, developing, and deploying enterprise LLM-powered and generative AI applications, including agentic AI workflows, multi-agent orchestration, and retrieval-augmented generation (RAG).
- Experience designing and implementing multi-agent AI systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent technologies, including Responder–Evaluator–Reporter workflows, model comparison, and AI output verification.
- Experience with LLM prompt engineering, prompt version management, structured generation, tool/function calling, agent execution controls, and human-in-the-loop workflows.
- Strong Python software engineering skills, including RESTful API development, asynchronous programming, modular application design, and modern software development practices.
- Experience designing distributed applications, microservices, or event-driven architectures and integrating AI capabilities with structured and unstructured enterprise data through secure APIs and retrieval architectures.
- Experience implementing secure, permission-aware enterprise data integrations, including authentication, authorization, identity propagation, data governance, source traceability, and auditability.
- Experience designing and evaluating reliable, explainable AI systems, including factual grounding, source citations, hallucination mitigation, model performance evaluation, and responsible human oversight.
- Experience with LLMOps and AI assurance practices, including automated regression testing, prompt-injection defenses, model/prompt version tracking, application observability, and performance monitoring.
- Experience with cloud-native architectures and containerized application deployment using Docker, AWS or Azure, Kubernetes, Terraform, Helm, or comparable technologies.
- Experience implementing CI/CD pipelines, automated testing, version control, and software configuration management to support secure, reliable application delivery.
- Demonstrated ability to translate technical and mission requirements into scalable system architectures, implementation plans, interface specifications, and engineering deliverables.
- Experience leading technical design and code reviews, troubleshooting complex software integrations, mentoring engineers, and providing hands-on technical guidance throughout the software development lifecycle.
- Strong written and verbal communication skills, including experience producing technical documentation, presenting architectural decisions, and supporting technical demonstrations, Government acceptance testing, and operational pilot deployments.
Preferred Qualifications:
- Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical discipline.
- Experience integrating enterprise AI applications with Palantir, Databricks, Elasticsearch, or similar governed data and analytics platforms.
- Experience developing Python backend services using FastAPI, Pydantic, asyncio, or comparable frameworks.
- Experience supporting secure software development and deployment in Federal Government, Department of Defense, Intelligence Community, or Department of Homeland Security environments.
- Familiarity with Government cybersecurity, privacy, accessibility, and software authorization processes.
- Experience adapting existing AI research, algorithms, prototypes, or software components into operational enterprise applications.
- Experience supporting AI-enabled document processing, intelligent search, case management, investigative analytics, or automated report generation.
Benefits:
Expression offers competitive salaries and benefits, such as:
- 401k matching
- PPO and HDHP medical/dental/vision insurance
- Education reimbursement
- Complimentary life insurance
- Generous PTO and holiday leave
- Onsite office gym access
- Commuter Benefits Plan
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
hatch I.T. is partnering with Expression to find an AI Architect (Technical Lead). See details below:
About The Role:
Expression is seeking an experienced AI Architect to serve as Technical Lead designing and technically integrating advanced Artificial Intelligence (AI) and Large Language Model (LLM) capabilities supporting the Department of Homeland Security (DHS).
This role will support the development and integration of secure, mission-focused AI agents within the DHS AI environment. The selected candidate will lead the adaptation of multi-agent AI capabilities, including intelligent workflow orchestration, retrieval-augmented generation (RAG), model evaluation, and governed enterprise data integration, to enhance investigative analysis, information retrieval, report generation, and human decision support.
The ideal candidate is a hands-on AI architect and technical leader with extensive experience designing and delivering enterprise AI applications. You are equally comfortable defining system architecture, developing and reviewing production-quality software, integrating LLMs with enterprise data systems, and mentoring engineers through complex technical challenges.
This position requires a strong understanding of modern AI engineering, distributed application architectures, secure API development, and responsible AI deployment within highly regulated environments. You will work closely with AI engineers, data engineers, program leadership, and Government stakeholders to deliver reliable, explainable, secure, and scalable AI capabilities.
Location and Clearance:
Clearance: Top Secret/SCI required
Location: Shirlington, VA
About the Company:
Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s “Perpetual Innovation” culture focuses on creating immediate and sustainable value for their clients via agile delivery of tailored solutions built through constant engagement with their clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.
Responsibilities:
- Lead the technical architecture, design, and implementation of enterprise AI and agentic AI solutions within the Government's existing AI environment, emphasizing reuse of approved infrastructure, services, and model endpoints.
- Define scalable, secure, and maintainable software architectures integrating LLMs, specialized AI agents, enterprise data services, APIs, and human-in-the-loop workflows.
- Design and implement multi-agent orchestration frameworks, including Responder–Evaluator–Reporter workflows, model selection, prompt management, tool invocation, and structured output validation.
- Lead the integration of Government-approved frontier AI models through authorized endpoints, ensuring appropriate model configuration, version management, performance evaluation, and controlled execution.
- Architect retrieval-augmented generation (RAG) solutions that integrate authorized enterprise data sources while preserving source attribution, access controls, data lineage, and traceability.
- Guide integration with Palantir, Databricks, Elasticsearch, and other approved Government data services through secure APIs and governed interfaces.
- Design secure AI agent execution frameworks incorporating identity propagation, role-based and purpose-based access controls, bounded tool permissions, approval checkpoints, execution limits, and safe failure mechanisms.
- Develop and review production-quality backend services, APIs, and orchestration components using Python and modern software engineering practices.
- Lead architecture and code reviews, resolve complex integration challenges, and establish engineering standards for maintainability, reliability, security, and performance.
- Design evaluation and testing approaches for LLM and multi-agent applications, including factual accuracy, consistency, explainability, latency, scalability, and computational cost.
- Establish observability, logging, prompt and model version tracking, and auditability across AI workflows, ensuring AI-generated outputs can be traced to supporting sources and reviewed by authorized personnel.
- Collaborate with cybersecurity, DevSecOps, privacy, and Government stakeholders to align system designs with approved deployment pipelines, security controls, authorization requirements, and release processes.
- Support the adaptation of existing AI algorithms, prompts, and software components into Government-approved investigative workflows, documenting technical lineage, modifications, and integration requirements.
- Produce solution architecture documents, system design specifications, interface control documents, data-flow diagrams, technical evaluations, and engineering implementation guidance.
- Support technical demonstrations, prototype evaluations, user acceptance activities, and Government design reviews.
- Provide technical leadership and mentorship to AI engineers and data engineers while maintaining meaningful hands-on involvement in architecture, development, debugging, and integration.
- Evaluate proposed third-party AI tools, frameworks, and software components for technical suitability, security implications, integration complexity, and reuse of existing Government capabilities, coordinating recommendations through established approval processes.
Qualifications:
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical field, or equivalent relevant professional experience.
- 12+ years of professional experience in software engineering, AI engineering, data engineering, or enterprise application development, including 3+ years in software architecture or technical leadership roles.
- Demonstrated hands-on experience architecting, developing, and deploying enterprise LLM-powered and generative AI applications, including agentic AI workflows, multi-agent orchestration, and retrieval-augmented generation (RAG).
- Experience designing and implementing multi-agent AI systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent technologies, including Responder–Evaluator–Reporter workflows, model comparison, and AI output verification.
- Experience with LLM prompt engineering, prompt version management, structured generation, tool/function calling, agent execution controls, and human-in-the-loop workflows.
- Strong Python software engineering skills, including RESTful API development, asynchronous programming, modular application design, and modern software development practices.
- Experience designing distributed applications, microservices, or event-driven architectures and integrating AI capabilities with structured and unstructured enterprise data through secure APIs and retrieval architectures.
- Experience implementing secure, permission-aware enterprise data integrations, including authentication, authorization, identity propagation, data governance, source traceability, and auditability.
- Experience designing and evaluating reliable, explainable AI systems, including factual grounding, source citations, hallucination mitigation, model performance evaluation, and responsible human oversight.
- Experience with LLMOps and AI assurance practices, including automated regression testing, prompt-injection defenses, model/prompt version tracking, application observability, and performance monitoring.
- Experience with cloud-native architectures and containerized application deployment using Docker, AWS or Azure, Kubernetes, Terraform, Helm, or comparable technologies.
- Experience implementing CI/CD pipelines, automated testing, version control, and software configuration management to support secure, reliable application delivery.
- Demonstrated ability to translate technical and mission requirements into scalable system architectures, implementation plans, interface specifications, and engineering deliverables.
- Experience leading technical design and code reviews, troubleshooting complex software integrations, mentoring engineers, and providing hands-on technical guidance throughout the software development lifecycle.
- Strong written and verbal communication skills, including experience producing technical documentation, presenting architectural decisions, and supporting technical demonstrations, Government acceptance testing, and operational pilot deployments.
Preferred Qualifications:
- Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical discipline.
- Experience integrating enterprise AI applications with Palantir, Databricks, Elasticsearch, or similar governed data and analytics platforms.
- Experience developing Python backend services using FastAPI, Pydantic, asyncio, or comparable frameworks.
- Experience supporting secure software development and deployment in Federal Government, Department of Defense, Intelligence Community, or Department of Homeland Security environments.
- Familiarity with Government cybersecurity, privacy, accessibility, and software authorization processes.
- Experience adapting existing AI research, algorithms, prototypes, or software components into operational enterprise applications.
- Experience supporting AI-enabled document processing, intelligent search, case management, investigative analytics, or automated report generation.
Benefits:
Expression offers competitive salaries and benefits, such as:
- 401k matching
- PPO and HDHP medical/dental/vision insurance
- Education reimbursement
- Complimentary life insurance
- Generous PTO and holiday leave
- Onsite office gym access
- Commuter Benefits Plan
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
See All 25 Technical Architect Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
Find Technical Architect JobsTechnical Architect Jobs by City in Virginia
Where Virginia roles are concentrated, by current openings.
Technical Architect Job Market in Virginia
A snapshot from current Virginia openings, updated as new roles post.
Who's Hiring
What Virginia Employers Look For
The qualifications that appear most often in technical architect jobs across Virginia.
- Bachelor's degree in computer science, information systems, or a related engineering field
- Hands-on experience designing and implementing large-scale enterprise or cloud architectures
- Proficiency with cloud platforms such as AWS, Azure, or Google Cloud and associated services
- Active or obtainable security clearance preferred for federal and defense contracting roles
- Strong communication skills to translate technical architecture into executive-level documentation
- Experience with infrastructure-as-code tools, DevSecOps pipelines, and modern integration patterns
Technical Architect Jobs in Virginia: Frequently Asked Questions
How do you become a technical architect in Virginia?
Most technical architects in Virginia reach the role by progressing from software engineering, systems administration, or infrastructure positions into architecture responsibilities over several years. While there is no Virginia-specific state license required for the title, employers in the region, particularly defense contractors, strongly favor candidates holding industry certifications such as AWS Certified Solutions Architect, Microsoft Azure Solutions Architect Expert, or a TOGAF certification. A bachelor's degree in a technical field is the standard educational baseline.
How much do technical architects make in Virginia?
Technical architects in Virginia earn a median of about $141,340 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $85,050 for the lowest 10% to over $210,180 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire technical architects in Virginia?
Employers hiring technical architects in Virginia right now include Accenture Federal Services, Steampunk, and Agility Technologies, based on current listings on Migrate Mate as of November 2026. Virginia's dense concentration of federal agencies and defense contractors means many of these roles sit within large systems integrators or government IT consulting firms headquartered or regionally anchored in Northern Virginia.
Which Virginia cities have the most technical architect jobs?
Reston, McLean, and Arlington have the most technical architect openings in Virginia. Northern Virginia dominates because of its proximity to federal agencies, the Pentagon, and the high density of defense and intelligence contractors based in Tysons, Reston, and Herndon, while Richmond draws enterprise and financial sector demand and Hampton Roads supports Navy and joint-force IT programs.
Are there remote technical architect jobs in Virginia?
Yes, and more than most technical fields. About 75% of technical architect openings tied to Virginia are remote or hybrid as of November 2026, reflecting the largely advisory and design-focused nature of the work. Architecture tasks such as solution design, documentation, and stakeholder review sessions translate well to distributed work, though roles with active security clearances or on-site integration responsibilities are more likely to require in-person presence.
How can I get hired as a technical architect in Virginia with little or no experience?
The most realistic entry path is lateral movement from a hands-on technical role, such as systems engineer, cloud engineer, or DevOps practitioner, where you already influence system design decisions. Large Northern Virginia contractors like Leidos, SAIC, and General Dynamics IT run associate or junior architect programs and hire new graduates with strong cloud certification portfolios into technical specialist roles that feed into architecture career tracks. Building a documented portfolio of architecture diagrams and design decisions, even from personal or academic projects, significantly strengthens early applications.
Where can I find and apply to technical architect jobs in Virginia?
You can find and apply to technical architect jobs in Virginia on Migrate Mate, which lists current Virginia openings across Northern Virginia, Richmond, Hampton Roads, and beyond. Find roles that fit your experience and specialty and apply directly to the employers posting them.
See All 25 Technical Architect Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
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