Weekend Software Developer Jobs in Virginia (NOW HIRING)

Software Developer
Practice: Software Development & Support / Digital
Company: Guidehouse
Location: Remote
Security and Work Authorization Requirements
• Must be able to obtain and maintain a Federal or Department of Defense Public Trust.
• Candidates must receive approved Public Trust adjudication before onboarding with Guidehouse.
• Candidates with an active Public Trust or current Federal suitability are preferred.
• Must be authorized to work in the United States without sponsorship.
Position Overview
Guidehouse is seeking a mid-level Software Developer with AI engineering capabilities to support the modernization of a large-scale GrantSolutions application portfolio through phased, low-risk delivery.
This is a hands-on software development role focused on modernizing mission-critical legacy applications while maintaining business continuity and interoperability with existing systems. The Software Developer will enhance and refactor legacy applications, build cloud-hosted services using modern programming languages and frameworks, and develop production-ready AI capabilities that improve information access, automate workflows, and augment user decision-making.
The developer will design, build, test, deploy, and support application and AI-enabled capabilities using technologies best suited to each solution. These may include Python, Java, JavaScript, TypeScript, C#/.NET, Go, or comparable technologies.
Modern capabilities will coexist with legacy applications and databases through an integrated data layer that provides governed, reusable access to shared data through APIs, events, data services, canonical models, transformation components, and AI-ready knowledge services.
Working closely with Solution Architects, Product Owners, data engineers, security teams, DevSecOps engineers, application teams, vendors, and Federal stakeholders, the Software Developer will:
• Incrementally refactor or replace legacy functionality
• Preserve essential business rules and compliance controls
• Reduce point-to-point dependencies
• Responsibly integrate AI into business workflows
• Deliver secure, maintainable, AWS-based solutions
The role is primarily a software development position, with responsibility for application code, APIs, events, reusable data and AI services, transformation logic, automated testing, AI evaluation, monitoring, and production support.
What You Will Do
Legacy Application Modernization
• Analyze legacy applications, data structures, interfaces, dependencies, and business rules to identify safe modernization increments.
• Enhance and refactor legacy applications and databases while developing new APIs, services, automation, and cloud-native components.
• Use appropriate modern programming languages and frameworks, including Python, Java, JavaScript, TypeScript, C#/.NET, Go, or comparable technologies.
• Implement phased modernization patterns that allow modern and legacy capabilities to operate concurrently without disrupting mission operations.
• Safely expose legacy capabilities and progressively separate tightly coupled application and data components.
• Preserve validated business rules, operational processes, and compliance controls throughout modernization.
Application and Service Development
• Develop modern application modules, microservices, APIs, reusable services, automation components, and cloud-hosted capabilities.
• Design versioned API, event, and data contracts that decouple consumers from legacy implementation details.
• Support controlled schema evolution across legacy applications, modern services, vendor platforms, and analytics capabilities.
• Develop resilient services using retries, timeouts, idempotency, dead-letter queues, transaction controls, and failure-recovery mechanisms.
• Implement secure authentication, authorization, encryption, secrets management, and least-privilege access across application and data interfaces.
Data Integration and Interoperability
• Build and maintain an integrated data layer that provides consistent, governed access to shared data.
• Develop reusable data services, canonical data models, APIs, events, and transformation components.
• Establish consistent data contracts and support synchronization and traceability across systems of record.
• Develop interoperability between legacy applications, modern services, vendor platforms, and analytics capabilities.
• Implement synchronous APIs, asynchronous messaging, events, batch processing, and change-data patterns.
• Perform data mapping, validation, transformation, lineage, reconciliation, synchronization, error handling, and auditing.
AI Engineering
• Design, prototype, and productionize AI capabilities when appropriate to the business need.
• Develop solutions involving retrieval-augmented generation, semantic search, document intelligence, classification, summarization, intelligent assistants, and agent-supported workflows.
• Integrate foundation models and machine-learning services with enterprise applications, APIs, and governed data.
• Use prompt orchestration, embeddings, vector search, tools, and model-agnostic service patterns.
• Develop AI evaluation suites and operational controls covering:
• Accuracy
• Groundedness
• Relevance
• Latency
• Cost
• Security
• Privacy
• Prompt injection
• Sensitive-data exposure
• Model drift
• Other use-case-specific risks
• Implement responsible AI controls, including guardrails, traceability, audit logging, prompt and model versioning, human-in-the-loop review, fallback behavior, and ongoing monitoring.
• Ensure AI capabilities align with organizational and Federal security, privacy, data-use, and responsible AI requirements.
Testing and Delivery
• Create unit, integration, contract, regression, and performance tests.
• Verify business behavior and end-to-end interoperability across applications, APIs, events, databases, cloud services, and legacy systems.
• Use CI/CD pipelines, infrastructure as code, code reviews, automated security scanning, and feature controls.
• Deliver application and infrastructure changes safely, consistently, and repeatedly.
• Participate in Agile development activities with architects, developers, data engineers, DevSecOps engineers, security teams, vendors, product teams, and Federal stakeholders.
Monitoring and Production Support
• Instrument application and data flows with centralized logging, metrics, tracing, health checks, alerts, and operational dashboards.
• Troubleshoot defects across:
• Application code
• Data flows
• APIs and events
• Databases
• AWS services
• Identity and access controls
• Network paths
• Deployment environments
• Support production operations and diagnose complex integration and interoperability issues.
Documentation
• Document code design, data models, mappings, interface contracts, migration decisions, and implementation notes.
• Maintain test evidence, deployment procedures, API documentation, interface specifications, and operational runbooks.
• Prepare support handoff materials for long-term operations and maintenance teams.
Required Qualifications
• Bachelor's degree.
• Five to eight years of software development experience, including legacy application enhancement or modernization, backend service development, data integration, and production support.
• Strong hands-on proficiency with one or more modern programming languages and associated frameworks, such as:
• Python
• Java
• JavaScript or TypeScript
• C#/.NET
• Go
• Comparable modern technologies
• Strong experience with SQL, RESTful API development, automated testing, and maintainable software design.
• Experience engineering AI-enabled applications using foundation-model APIs or machine-learning services.
• Hands-on experience with prompt design, retrieval-augmented generation, embeddings, vector search, AI evaluation, guardrails, and production monitoring.
• Ability to integrate AI services with enterprise applications and governed data.
• Understanding of security, privacy, data-use restrictions, traceability, human review, and responsible AI controls throughout the solution lifecycle.
• Experience analyzing and modifying legacy code, extracting business rules, resolving technical debt, and delivering incremental modernization while legacy and modern systems coexist.
• Experience developing AWS-based applications using services such as:
• API Gateway
• Lambda
• ECS or EKS
• SQS
• SNS
• EventBridge
• Step Functions
• DynamoDB
• CloudWatch
• Related integration and observability services
• Experience implementing secure integrations using OAuth 2.0, OpenID Connect, SAML, JWT, or similar authentication and authorization technologies.
• Strong understanding of enterprise integration patterns, API design, event-driven architecture, messaging systems, and asynchronous communication.
• Experience with messaging technologies such as SQS, SNS, EventBridge, Kafka, or comparable platforms.
• Strong experience with relational databases such as Oracle, including:
• Data modeling
• Query development
• SQL optimization
• Transactions
• Troubleshooting
• Performance tuning
• Working knowledge of NoSQL databases such as DynamoDB, MongoDB, Cassandra, or similar distributed data stores.
• Ability to design domain models and apply domain-driven design principles to complex business applications.
• Experience building an integrated data layer using:
• Reusable data services
• Canonical data models
• API and event contracts
• Mapping and transformation
• Validation
• Synchronization
• Data lineage
• Reconciliation
• Experience developing, testing, troubleshooting, and supporting distributed applications across APIs, databases, cloud services, and legacy systems.
• Familiarity with CI/CD pipelines, automated testing, Git-based source control, DevSecOps practices, software development lifecycle processes, Agile delivery, and release management.
• Experience provisioning AWS resources through infrastructure as code and deploying application changes through automated CI/CD pipelines.
• Ability to interpret architecture guidance, interface specifications, API contracts, data mappings, user stories, acceptance criteria, and technical design documentation.
• Strong analytical and problem-solving skills.
• Ability to diagnose and resolve complex integration and interoperability issues involving applications, APIs, data flows, identity controls, databases, AWS services, network paths, and deployment environments.
• Strong technical documentation skills.
• Ability to collaborate effectively with Solution Architects, developers, DevSecOps engineers, data teams, security teams, vendors, Product Owners, Scrum Masters, Federal stakeholders, and business stakeholders.
• Self-motivated, adaptable, and able to operate effectively in a fast-paced environment with appropriate guidance from technical leads.
• Must be able to obtain and maintain a Federal or DoD Public Trust.
• Must receive approved Public Trust adjudication before onboarding with Guidehouse.
• Must be authorized to work in the United States without sponsorship.
Preferred Qualifications
• Experience supporting enterprise or government platform modernization initiatives.
• Experience supporting Federal or government IT programs involving:
• Legacy system modernization
• Shared services
• Interoperability
• Cloud adoption
• Data governance
• Phased capability delivery
• Experience operating in regulated AWS environments, including FedRAMP, NIST SP 800-53, FIPS, audit logging, and AWS GovCloud, where applicable.
• Experience with API documentation tools, API gateways, data integration platforms, ETL or ELT patterns, message queues, workflow automation, or integration monitoring dashboards.
• Relevant cloud, Agile, software development, data, or security certifications, such as:
• AWS Certified Developer
• AWS Certified Solutions Architect, Associate
• SAFe certification
• Certified ScrumMaster
• CompTIA Security+
• Comparable certifications
• Experience working in a forward-deployed or customer-embedded engineering model.
• Experience working directly with mission users, Product Owners, and subject-matter experts to clarify ambiguous problems and rapidly deliver usable solutions.
• Ability to move from technical discovery and prototyping through production hardening, deployment, documentation, training, and transfer to long-term support teams.
• Experience facilitating technical demonstrations, gathering user feedback, and iterating on capabilities through short delivery cycles.
• Experience prototyping or integrating generative AI capabilities using AWS Bedrock or comparable enterprise AI platforms.
• Understanding of privacy, security, data-use restrictions, and responsible AI considerations in Federal or regulated environments.
• Experience with AI evaluation, prompt and model versioning, guardrails, monitoring, human-in-the-loop review, and mitigation of hallucination or unsafe-output risks.
Experience using generative AI and AI-assisted development tools to accelerate the software development lifecycle, including requirements analysis, solution design, code generation and modernization, automated testing, documentation, code review, troubleshooting, and release readiness, while applying app