Senior UX Developer (NIH Data Lakehouse Support)

📍 Job Overview

Job Title: Senior Front-End Product Engineer (NIH Data Lakehouse Support)

Company: General Dynamics Information Technology (GDIT)

Location: Remote Eligible (United States)

Job Type: Full-time

Category: Software Engineering / Product Engineering / UX/UI Design

Date Posted: 2026-08-10

Experience Level: 5+ years

Remote Status: Fully Remote

🚀 Role Summary

• Lead the end-to-end product development lifecycle for data-rich and AI-enabled applications supporting the National Institutes of Health (NIH).

• Architect and build high-performance, accessible, and secure React and Next.js applications, focusing on user experience and mission impact.

• Collaborate closely with NIH stakeholders, domain experts, designers, data scientists, and AI engineers to define and deliver innovative solutions.

• Drive human-centered discovery through user research, prototyping, and iterative feedback loops to ensure product-market fit and user satisfaction.

• Own the delivery, operation, and continuous improvement of front-end applications deployed across major cloud environments (Azure, AWS, Databricks Apps).

📝 Enhancement Note: This role is positioned as a Senior Front-End Product Engineer, emphasizing a blend of product ownership, UX/UI design, and deep front-end development expertise. The focus on NIH and data lakehouse support indicates a need for individuals comfortable with complex data environments, scientific applications, and potentially sensitive government data. The "engineering-first" approach suggests a preference for hands-on developers who can also influence product direction.

📈 Primary Responsibilities

• Lead human-centered discovery processes, including user interviews, contextual inquiry, workflow observation, task analysis, and collaborative workshops with NIH mission users and stakeholders.

• Translate research findings into clear personas, jobs-to-be-done, journey maps, service blueprints, information architecture, task flows, and actionable product hypotheses.

• Rapidly prototype user experiences from sketches and Figma concepts to high-fidelity coded prototypes, using feedback to prioritize production development.

• Plan and facilitate usability studies, accessibility reviews, design critiques, and behavioral analysis, translating insights into prioritized product and engineering decisions.

• Architect, build, and maintain production-ready React and Next.js applications using TypeScript, leveraging modern features like the App Router, Server Components, Server Functions, streaming, and advanced caching strategies.

• Develop responsive, adaptive, and accessible user interfaces using semantic HTML, modern CSS (e.g., Tailwind CSS), design tokens, accessible component primitives, and purposeful motion.

• Engineer data-intensive experiences such as dashboards, exploratory search interfaces, complex forms, virtualized tables, visual analytics, and collaboration workflows, ensuring users can interact with data models intuitively.

• Design and implement AI-native experiences, including copilots, RAG and agentic workflows, assisted analysis, and generative interfaces with streaming feedback, source attribution, provenance, clear limitations, and human approval points.

• Integrate GraphQL, REST, and OpenAPI services, event streams, and back-end capabilities using generated types, runtime validation, resilient error handling, and secure authentication/authorization patterns.

• Strategically manage state across URL, server, component, form, or shared client states, implementing efficient caching, synchronization, optimistic interaction, and recovery mechanisms.

• Build and evolve a reusable design system and component platform (e.g., in Storybook) to ensure consistency, accessibility, and faster delivery across the team.

• Own the full delivery pipeline from local development to production across Azure, AWS, and Databricks Apps, selecting appropriate managed, serverless, or container-based approaches.

• Automate build, test, security, and deployment pipelines, utilizing infrastructure as code, dependency controls, feature flags, and progressive delivery methods.

• Instrument applications with comprehensive logging, metrics, traces, error reporting, product analytics, and Core Web Vitals to monitor user experience and drive actionable insights.

• Develop a balanced quality strategy encompassing unit, component, contract, accessibility, visual, performance, and end-to-end testing, integrating production reliability and incident learning into the quality framework.

• Set a forward-looking front-end roadmap, document architectural decisions, communicate tradeoffs effectively, and maintain a modern platform without unnecessary novelty.

• Partner directly with users and leaders, clearly explaining technical choices, inviting constructive dissent, and fostering alignment across design, product, data, AI, security, and engineering teams.

• Mentor engineers and designers, lead design and code reviews, establish front-end quality standards, and create efficient development pathways for the team.

• Responsibly leverage AI-assisted design and development tools to accelerate workflows while maintaining human review, security, traceability, and engineering judgment.

• Measure and report on key outcomes such as user adoption, task success rates, time on task, error rates, accessibility compliance, performance metrics, reliability, user confidence, and overall mission value.

📝 Enhancement Note: The responsibilities are extensive and highlight a "product engineer" mindset, where the individual is expected to contribute to product strategy and user research, not just coding. The emphasis on AI-native experiences, data visualization, and cloud deployment across multiple platforms (Azure, AWS, Databricks) is critical. The requirement for end-to-end ownership from discovery to operation is a key differentiator.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong portfolio and demonstrable experience in front-end development, UX/UI design, and product engineering are paramount. Relevant certifications in cloud technologies or specific front-end frameworks could be beneficial.

Experience: 5+ years of professional front-end or product engineering experience, with a proven track record of shipping and owning production React applications.

Required Skills:

• Deep expertise in React, TypeScript, JavaScript, semantic HTML, and modern CSS.

• Proficiency in building responsive, adaptive, and accessible user interfaces compliant with WCAG and Section 508 standards.

• Hands-on experience with modern React frameworks and patterns, including Next.js (App Router, React Server Components, Server Functions), and state management solutions (e.g., TanStack Query, Zustand, Jotai).

• Experience in designing and implementing user-centered discovery processes, including user research, persona development, and journey mapping.

• Proven ability to prototype at various fidelities (sketches, Figma, coded prototypes) and iterate based on user feedback.

• Experience in architecting and building data-intensive applications, including dashboards and complex forms.

• Familiarity with API integration (GraphQL, REST, OpenAPI) and data handling patterns.

• Experience with component-driven development and building/maintaining design systems or reusable component libraries (e.g., Storybook).

• Practical knowledge of deploying and operating modern web applications in at least one major cloud environment (Azure, AWS, or Databricks Apps).

• Strong understanding of front-end performance optimization, web performance budgets, and Core Web Vitals.

• Experience with automated testing frameworks (e.g., Vitest, React Testing Library, Playwright) and CI/CD pipelines.

• Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly.

• Demonstrated technical leadership, curiosity, self-direction, and comfort with ambiguity.

• Ability to obtain a Public Trust clearance. Preferred Skills:

• Direct experience with Databricks Apps, Databricks SQL, Unity Catalog, model serving, or lakehouse patterns.

• Experience designing and shipping trustworthy AI products using RAG, multimodal models, agents, evaluation, source grounding, human review, and responsible AI patterns.

• Familiarity with biomedical, scientific, clinical, research, or public-health data; knowledge of FAIR data principles, FHIR, data provenance, or research data governance.

• Advanced data visualization experience with high-dimensional, graph, temporal, or geospatial datasets.

• Experience with advanced browser capabilities like Web Workers, WebAssembly, Canvas, WebGL, or WebGPU.

• Experience with product experimentation, feature flags, A/B testing, and product analytics.

• Experience delivering into secure or regulated federal environments, including DevSecOps controls.

• History of raising the bar through technical strategy, mentoring, open-source contributions, or front-end platform enablement.

📝 Enhancement Note: The emphasis is on deep React and TypeScript expertise, coupled with product thinking and UX research capabilities. The "5+ years" is a baseline, with the portfolio and demonstrated impact being more critical. Preferred skills strongly align with the specific NIH mission and advanced data/AI challenges.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• A comprehensive portfolio showcasing end-to-end product development ownership, including discovery artifacts (personas, user journeys, research synthesis), design documentation (wireframes, prototypes, UI mockups), architectural decisions, and shipped code examples.

• Case studies that clearly articulate the problem, the proposed solution, the design and technical tradeoffs made, the implementation details, and the measurable outcomes or impact of the work.

• Demonstrations of user-centered design principles applied to complex data or AI-driven applications.

• Evidence of building and maintaining reusable components, design systems, or front-end platforms.

• Examples of performance optimization, accessibility compliance, and robust error handling in shipped applications. Process Documentation:

• Documented workflows for user research, ideation, prototyping, design critique, and usability testing.

• Clear architectural decision records (ADRs) for significant front-end design choices.

• Examples of automated testing strategies and CI/CD pipeline configurations.

• Evidence of instrumenting applications for telemetry, logging, metrics, and error tracking.

• Process for continuous improvement based on production monitoring, user feedback, and incident analysis.

📝 Enhancement Note: The portfolio is not just about code samples but about demonstrating a holistic product engineering process from user needs to operational excellence. The ability to articulate tradeoffs and measure impact is crucial.

💵 Compensation & Benefits

Salary Range: $110,500 - $149,500 annually.

Explanation: This range is based on the provided salary information. It is important to note that actual compensation will be determined by factors such as candidate experience, geographic location, and specific contractual requirements, and may fall outside this stated range. The role is full-time, implying a standard annual salary structure.

Benefits:

• Comprehensive medical plan options, with some including Health Savings Accounts (HSAs).

• Dental plan options.

• Vision plan.

• 401(k) plan with pre- and post-tax contribution options, including a company match.

• Generous paid time off (PTO) including vacation, sick, and personal time.

• 10 paid holidays per year.

• Paid parental, military, bereavement, and jury duty leave.

• New employees typically receive 15 days of paid leave annually, prorated based on hire date.

• Paid Family Leave program providing up to 160 hours in a rolling 12-month period.

• Short-term and long-term disability benefits.

• Life insurance, accidental death and dismemberment (AD&D) insurance.

• Personal accident insurance.

• Critical illness insurance.

• Business travel and accident insurance.

Working Hours: 40 hours per week. The role description indicates a "full flex work weeks where possible," suggesting flexibility in daily scheduling while maintaining the 40-hour commitment.

📝 Enhancement Note: The provided salary range is specific and noted as a guideline. The benefits package is extensive, covering health, retirement, time off, and various insurance types, which are standard for a large, established company like GDIT. The "full flex work weeks" note adds a layer of flexibility to the standard 40-hour week.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology Services & Consulting, Government Contracting, Software Development, Data & AI. GDIT operates within the IT and professional services sector, with a significant focus on supporting U.S. government agencies, particularly in defense, intelligence, and health.

Company Size: GDIT is a large enterprise, employing tens of thousands of individuals globally, indicating a structured corporate environment with established processes and a wide array of resources. This size offers stability and broad career opportunities but may also mean navigating larger organizational structures.

Founded: While the exact founding date of GDIT as it exists today isn't explicitly stated in the provided data, its history involves significant mergers and acquisitions, with its roots tracing back decades in government contracting. This longevity suggests a deep understanding of government procurement and operational requirements.

Team Structure:

• The role operates within a software engineering or product engineering team, likely supporting a larger program for the NIH.

• The team is expected to be cross-functional, including product managers, UX designers, data scientists, AI engineers, back-end engineers, and platform specialists.

• Reporting structure is likely to a front-end lead, engineering manager, or program director, with direct collaboration with NIH mission stakeholders.

• Collaboration is expected to be high-ownership, direct, fast-learning, and focused on thoughtful tradeoffs. Methodology:

• Data Analysis & Insights: Emphasis on leveraging telemetry, user analytics, and performance metrics to drive product decisions and continuous improvement.

• Workflow Planning & Optimization: Focus on human-centered design, mapping user journeys, and optimizing workflows for efficiency and clarity in complex mission environments.

• Automation & Efficiency: Utilization of CI/CD, infrastructure as code, and AI-assisted tools to streamline development, deployment, and operational processes.

Company Website: https://www.gdit.com/

📝 Enhancement Note: GDIT's background in government contracting implies a strong adherence to security, compliance, and process. The specific team culture described ("high ownership, direct collaboration, fast learning, thoughtful tradeoffs") suggests an agile, product-focused environment within this larger corporate structure, aiming to bring startup-like agility to government missions.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior-level Product Engineer role. It signifies a position requiring significant autonomy, technical depth, and the ability to influence product direction and technical strategy. It's a key individual contributor role with potential leadership responsibilities in mentoring and setting standards.

Reporting Structure: The role reports into a management structure likely overseeing front-end development or product engineering for the NIH program. Direct collaboration with NIH mission stakeholders is a critical aspect, indicating influence beyond the immediate team.

Operations Impact: The role has a direct impact on the effectiveness and efficiency of biomedical research and public health initiatives at the NIH by building the "front door" to discovery and data. Success means making complex workflows obvious and trustworthy for thousands of users, directly contributing to scientific advancement and public service.

Growth Opportunities:

• Operations Skill Advancement: Deepen expertise in modern front-end architecture, AI-native UX, data visualization, and cloud-native development (Azure, AWS, Databricks).

• Industry Specialization: Become an expert in the unique challenges and opportunities within biomedical data science, AI for research, and federal health IT.

• Technical Leadership: Grow into roles such as Front-End Architect, Technical Lead, or Principal Engineer, mentoring junior team members and setting technical vision.

• Product Ownership: Transition towards more product management responsibilities or lead product strategy for specific feature sets or applications.

• Cross-functional Expertise: Develop a strong understanding of data science, AI engineering, cloud operations, and cybersecurity within a government context.

📝 Enhancement Note: The growth paths emphasize both deepening technical specialization and expanding into product leadership and strategic influence, particularly within the specialized domain of government health and research IT.

🌐 Work Environment

Office Type: Primarily a remote work environment. The job description explicitly states "Remote Eligible" and "Any Location / Remote." While there's a "MD, United States" location listed, the remote nature is heavily emphasized.

Office Location(s): While the role is remote, the company has a significant presence in Maryland, USA, which is often associated with government contracting hubs. The specific "MD HOME Office (MDHOME)" designation might refer to a home-based employee status within Maryland for administrative purposes, but the role itself is remote.

Workspace Context:

• Collaborative Environment: Expect a highly collaborative remote setting, relying heavily on digital collaboration tools for communication, design reviews, code reviews, and team meetings.

• Operations Tools & Technology: Access to a modern front-end development stack, cloud platforms (Azure, AWS, Databricks), and potentially specialized NIH systems. The company provides the necessary technological infrastructure for remote work.

• Team Interaction: Regular virtual stand-ups, sprint planning, retrospectives, and ad-hoc communication channels (e.g., Slack, Teams) to foster team cohesion and project alignment.

Work Schedule: Standard 40-hour work week, with a "full flex work weeks where possible" policy, allowing for flexibility in daily start and end times, provided work commitments and collaboration needs are met. This flexibility supports deep work and personal life integration.

📝 Enhancement Note: The remote nature is a key feature. Candidates should be comfortable with asynchronous communication and self-management in a distributed team. The mention of "MD HOME Office" might be an internal designation for employees based in Maryland, but the role itself is remote.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a recruiter screen to assess basic qualifications, experience, and cultural fit.

• Technical Interviews: Multiple rounds focusing on React, TypeScript, JavaScript fundamentals, architectural design, problem-solving, and data visualization/AI experience. Expect coding challenges and system design questions.

• Portfolio Review: A dedicated session where candidates present their portfolio, walking through case studies, explaining their process, design decisions, technical tradeoffs, and measured outcomes. This is a critical component.

• Behavioral/Situational Interviews: Questions assessing leadership, collaboration, handling ambiguity, user empathy, and experience with similar mission-critical projects.

• Hiring Manager/Team Lead Interview: Final discussion to assess overall fit, strategic thinking, and alignment with team goals.

Portfolio Review Tips:

• Curate Selectively: Choose 2-3 projects that best demonstrate your end-to-end product engineering capabilities, focusing on complexity, impact, and your specific role.

• Tell a Story: Structure your presentation around the problem, your process (discovery, design, development), the solutions and tradeoffs, and the measurable results. Use visuals effectively.

• Highlight Impact: Quantify outcomes wherever possible (e.g., "reduced task completion time by X%", "improved data accuracy by Y%", "increased user adoption by Z%").

• Explain Tradeoffs: Be ready to discuss why you made specific technical or design choices and what alternatives you considered. This shows critical thinking.

• Showcase Process: Demonstrate your understanding of human-centered design, agile development, and production operations.

• Address AI/Data: If applicable, clearly articulate your experience with AI-native interactions or complex data visualization challenges.

Challenge Preparation:

• Front-End Coding: Practice challenging algorithm and data structure problems within a React context. Be prepared for live coding exercises.

• System Design: Prepare to design scalable, performant, and accessible front-end architectures for data-intensive or AI-driven applications. Consider state management, API integrations, caching, and cloud deployment.

• UX/Product Thinking: Anticipate questions about user research, translating requirements into user flows, and designing intuitive interfaces for complex domains.

• Accessibility & Performance: Review best practices for WCAG compliance and Core Web Vitals optimization.

• Cloud & Operations: Understand basic concepts of CI/CD, infrastructure as code, and cloud service deployment relevant to front-end applications.

📝 Enhancement Note: The interview process heavily emphasizes the portfolio and the ability to articulate a complete product lifecycle. Candidates should prepare to demonstrate their end-to-end ownership and impact.

🛠 Tools & Technology Stack

Primary Tools:

• Core React & Language: React, Next.js (App Router, React Server Components, Server Functions), TypeScript, JavaScript, Node.js, pnpm.

• UI & Design Systems: Tailwind CSS, shadcn/ui, Base UI, React Aria or Radix UI, design tokens, Storybook, Figma.

• Data, State & Forms: GraphQL, REST, OpenAPI, GraphQL Code Generator, TanStack Query, Zod, URL state, Zustand or Jotai (for shared client state), React Hook Form, WebSockets, Server-Sent Events, streaming data patterns.

• Data Visualization & Scale: TanStack Table and Virtual, D3, Observable Plot, Vega-Lite, Apache ECharts, Canvas, WebGL or WebGPU (as needed), code splitting, virtualization.

• AI Experience Engineering: Tools and patterns for streaming model responses, RAG, agentic interactions, tool execution, source attribution, human-in-the-loop controls, and responsible AI UX.

• Quality & Accessibility: Vitest, React Testing Library, Playwright, Mock Service Worker, Storybook interaction/visual testing, automated accessibility checks, WCAG, Section 508.

• Cloud & Operations: Git, CI/CD, Docker, Terraform, Bicep or cloud development kits, Azure, AWS, Databricks Apps, OAuth, OpenID Connect, OpenTelemetry, centralized logs, metrics, traces, error tracking, feature flags, product analytics.

Analytics & Reporting:

• Product Analytics: Tools for tracking user behavior, feature adoption, and task success (specific tools not named but implied).

• Performance Monitoring: Core Web Vitals, browser performance profiling tools.

• Logging & Tracing: OpenTelemetry, centralized logging systems.

CRM & Automation: While not explicitly a CRM role, the integration of various services and the focus on operational efficiency suggest familiarity with automation principles and potentially workflow tools relevant to deployment and monitoring.

📝 Enhancement Note: This is a very detailed and modern tech stack. Candidates should highlight their proficiency in these specific technologies, especially Next.js App Router, React Server Components, Tailwind CSS, GraphQL, and cloud platforms. Experience with AI interaction patterns and data visualization libraries is a significant plus.

👥 Team Culture & Values

Operations Values:

• High Ownership: Taking full responsibility for product outcomes from conception to operation.

• Direct Collaboration: Working closely and transparently with users, stakeholders, and cross-functional team members.

• Fast Learning: Embracing new technologies, methodologies, and feedback to adapt and improve rapidly.

• Thoughtful Tradeoffs: Making informed decisions by balancing technical constraints, user needs, business goals, and security requirements.

• Clarity & Curiosity: Seeking to understand problems deeply and communicate solutions clearly.

• Inclusion & Constructive Feedback: Fostering an environment where diverse perspectives are valued and feedback is given and received positively.

• Excellent Craft: Striving for high-quality, performant, accessible, and maintainable code and user experiences.

• Data-Driven Decision Making: Using telemetry, analytics, and user feedback to guide product evolution.

• Efficiency & Optimization: Continuously seeking ways to improve processes, workflows, and application performance.

Collaboration Style:

• Cross-functional Integration: Seamless collaboration across design, product, data science, AI engineering, and back-end engineering teams.

• Process Review & Feedback: Regular design critiques, code reviews, and sprint retrospectives to ensure continuous improvement and knowledge sharing.

• Knowledge Sharing: Active participation in team discussions, documentation, and potentially internal tech talks or workshops.

• Experimentation: A culture that encourages thoughtful experimentation with new technologies and approaches, balanced with pragmatic delivery.

📝 Enhancement Note: The team culture emphasizes agility, ownership, and a high standard of technical and design craft within a government contracting context. The values are geared towards delivering impactful solutions efficiently and collaboratively.

⚡ Challenges & Growth Opportunities

Challenges:

• Ambiguity: Navigating complex, often ill-defined mission problems at the NIH, requiring strong initiative and problem-framing skills.

• Data Complexity: Working with large, diverse, and potentially sensitive biomedical datasets, requiring sophisticated data handling and visualization techniques.

• AI Integration: Designing trustworthy and effective user experiences for novel AI applications (RAG, agents) in a scientific context.

• Federal Environment: Adhering to strict security, compliance (Section 508), and operational standards within a government agency.

• Scalability & Performance: Ensuring applications remain performant and reliable for thousands of users interacting with data-rich interfaces.

• Cloud Heterogeneity: Managing deployments and operations across Azure, AWS, and Databricks Apps.

Learning & Development Opportunities:

• Operations Skill Advancement: Opportunities to master advanced React patterns, Next.js architecture, modern CSS, and cutting-edge AI UX design.

• Industry Specialization: Deep dive into the NIH's data science initiatives, biomedical research workflows, and the application of AI in scientific discovery.

• Mentorship & Leadership: Potential to mentor junior engineers, lead technical initiatives, and contribute to front-end strategy and platform development.

• Cloud & DevSecOps: Gaining hands-on experience with IaC, CI/CD, and operational best practices across multiple cloud providers in a secure government setting.

• Conferences & Training: GDIT likely offers opportunities for professional development, including attending industry conferences, workshops, and pursuing relevant certifications.

📝 Enhancement Note: The challenges are specific to the domain (NIH, AI, data) and the environment (government contracting, multi-cloud). The growth opportunities are substantial for an engineer looking to specialize in high-impact, technically complex areas.

💡 Interview Preparation

Strategy Questions:

• Operations Strategy: "How would you approach defining the front-end architecture for a new NIH data lakehouse application, considering scalability, security, and user experience?" "Describe a time you had to make a significant technical tradeoff in a front-end project. What was the situation, your decision, and the outcome?" "How do you balance rapid iteration with maintaining code quality and production stability in a mission-critical application?"

• Collaboration & Stakeholder Management: "How do you gather requirements from non-technical stakeholders for a complex technical project?" "Describe a situation where you had to influence product direction or technical decisions. How did you approach it?" "How do you handle constructive criticism or disagreements during design or code reviews?"

• Problem-Solving: "Walk me through how you would design a user interface for an AI-powered research assistant that needs to provide source attribution and handle potential model hallucinations." "How would you approach optimizing the performance of a data visualization dashboard that displays millions of data points?" "Describe a challenging bug you encountered in a React application. How did you diagnose and resolve it?"

Company & Culture Questions:

• "What interests you about working with the NIH and their mission?" "How do you see your skills contributing to GDIT's work in the government health sector?" "What are your expectations for team culture in a remote, government-contracting environment?" "How do you stay updated on the latest trends in front-end development, UX, and AI?" Portfolio Presentation Strategy:

• Structure for Impact: Begin with a brief overview of your career and highlight the projects you'll present. For each project, clearly state the problem, your role, the key challenges, your solution (design and technical), and the measurable impact.

• Visual Storytelling: Use screenshots, diagrams, interactive prototypes (if possible), and code snippets to illustrate your points. Explain why you made certain design or architectural choices.

• Quantify Results: Emphasize metrics and outcomes. If exact numbers aren't available, discuss qualitative improvements and user feedback.

• Demonstrate Process: Show your understanding of the full product lifecycle, from discovery and research to deployment and operations.

• Address Tradeoffs: Be prepared to discuss difficult decisions and the reasoning behind them. This demonstrates critical thinking and maturity.

• Tailor to the Role: Emphasize projects that showcase experience with complex data, AI interactions, accessibility, performance, and cloud deployment, aligning with the requirements of this Senior Front-End Product Engineer role.

📝 Enhancement Note: Interview questions will be highly scenario-based and focused on practical application of skills in a government/research context. The portfolio presentation is a key opportunity to showcase end-to-end ownership and impact.

📌 Application Steps

To apply for this Senior Front-End Product Engineer position:

• Submit your application through the provided Workday job portal link.

• Portfolio Customization: Tailor your resume and cover letter to highlight specific experiences relevant to React, Next.js, TypeScript, data visualization, AI UX, accessibility, and cloud environments, especially any government or health sector experience.

• Resume Optimization: Ensure your resume clearly articulates your 5+ years of experience, focusing on achievements and responsibilities that demonstrate end-to-end product ownership, technical leadership, and impact. Use keywords from the job description.

• Portfolio Preparation: Curate your portfolio to showcase 2-3 strong case studies that exemplify your ability to tackle complex problems, from user discovery and design to development and deployment. Be ready to present and discuss these in detail.

• Company Research: Familiarize yourself with GDIT's mission, values, and work in the government and health sectors. Understand the NIH's mission and strategic goals for data science. This will help you articulate your alignment during interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.