Modernization Software Developer

Job Title: Modernization Software DeveloperJob Category: EngineeringTime Type: Full timeMinimum Clearance Required to Start: Public TrustEmployee Type: RegularPercentage of Travel Required: Up to 10%Type of Travel: Local* * *

The Opportunity:

We are seeking an experienced Software Developer with hands-on software and AI engineering experience. The candidate will be responsible for modernizing mission-critical legacy applications while maintaining business continuity and interoperability with existing systems. The developer will design, build, test, and deploy modern application and AI-enabled capabilities using the programming languages, frameworks, models, and platforms best suited to each solution, such as Python, Java, JavaScript/TypeScript, C#/.NET, Go, or comparable technologies. These 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 with architects, data engineers, security, DevSecOps, product teams, and vendors, the developer incrementally refactors or replaces legacy functionality, responsibly integrates AI into business workflows, preserves essential business rules, reduces point-to-point dependencies, and delivers secure, maintainable AWS-based solutions.

Responsibilities:
As a mid-level Software Developer, utilize AI engineering capabilities to help modernize a large-scale GrantSolutions application portfolio through phased, low-risk delivery. The developer will enhance and refactor legacy applications, build new cloud-hosted services using modern languages and frameworks, and develop production-ready AI capabilities that improve information access, automate workflows, and augment user decision-making. The developer will implement interoperability between modern, AI-enabled, and legacy capabilities through an integrated data layer. The role is primarily a software development position, with responsibility for application code, reusable data and AI services, APIs, events, transformation logic, automated tests, AI evaluation, monitoring, and production support.

The Software Developer will translate architecture and data-governance standards into working software. The developer will expose legacy capabilities safely, develop modern modules and microservices, establish consistent data contracts, and support synchronization and traceability across systems of record. The candidate will collaborate with Solution Architects, Product Owners, application and data teams, vendors, security teams, and Federal stakeholders to deliver incremental modernization without disrupting ongoing operations. 
The candidate will:

• 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 using appropriate modern 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.
• Build and maintain an integrated data layer that provides consistent, governed access to shared data through APIs, events, reusable data services, canonical models, and transformation components.
• Develop interoperability between legacy applications, modern services, vendor platforms, and analytics capabilities using synchronous APIs, asynchronous messaging, events, batch processing, and change-data patterns.
• Implement data mapping, validation, transformation, lineage, reconciliation, synchronization, error handling, and auditability across systems of record.
• Design, prototype, and productionize AI capabilities such as retrieval-augmented generation, semantic search, document intelligence, classification, summarization, intelligent assistants, and agent-supported workflows when appropriate to the business need.
• Integrate foundation models and machine-learning services with enterprise applications, APIs, and governed data using prompt orchestration, embeddings, vector search, tools, and model-agnostic service patterns.
• Design versioned API, event, and data contracts that decouple consumers from legacy impl…