Remote Forensic Behavioral Science Jobs in West Virginia

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Job Description:

Senior Front-End Product Engineer

React + UX + Data & AI Experiences

Build the front door to biomedical discovery.

LOCATION : Remote Eligible

CLEARANCE : Public Trust or ability to obtain one

MISSION PARTNER : National Institutes of Health

What happens when biomedical data, modern AI, and exceptional product craft meet? The hard thing becomes clear, fast, and trustworthy.

GDIT is looking for a senior front-end product engineer who can take an ambiguous mission problem from first conversation to production - and keep improving it after launch. This is an engineering-first role for someone who is equally comfortable interviewing users, sketching a flow, challenging a product assumption, designing an interaction model, and shipping a high-performance React application used by thousands of people or more.

You will build data-rich and AI-enabled mission applications for the National Institutes of Health. You will not simply receive a mockup and turn it into code. You will help define the product: personas, journeys, information architecture, prototypes, design system, front-end architecture, delivery plan, telemetry, and production operations. The work will deploy across Azure, AWS, and Databricks Apps.

Our goal: users should feel that a difficult mission workflow just became obvious.

This role lives at the intersection of product design, UX research, front-end architecture, data visualization, AI interaction design, and cloud delivery. You will partner with NIH mission stakeholders, domain experts, product leaders, designers, data scientists, AI engineers, back-end engineers, and platform teams to decide what should be built and then make it real.

You will move fast, but not recklessly. You will use prototypes and evidence to reduce ambiguity, make thoughtful tradeoffs, and take responsibility for the quality, accessibility, security, reliability, and impact of what reaches users.

This is not a handoff role. It is an ownership role.

Lead human-centered discovery through interviews, contextual inquiry, workflow observation, task analysis, and collaborative workshops with mission users and stakeholders.

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

Prototype at the speed of learning - from sketches and Figma concepts to high-fidelity coded prototypes - and use feedback to decide what deserves production investment.

Plan and facilitate usability studies, accessibility reviews, design critiques, and behavioral analysis; translate findings into prioritized product and engineering decisions.

Engineer the product

Architect and build production React and Next.js applications using TypeScript, the App Router, Server Components, Server Functions, streaming, modern caching, and intentionally small client-side boundaries.

Create responsive, adaptive, accessible interfaces using semantic HTML, modern CSS, Tailwind CSS, design tokens, accessible component primitives, and purposeful motion.

Build data-intensive experiences - dashboards, exploratory search, complex forms, virtualized tables, visual analytics, collaboration workflows, and real-time or streaming interfaces - without making users wrestle with the data model.

Design AI-native experiences such as copilots, RAG and agentic workflows, assisted analysis, and generative interfaces with streaming feedback, source attribution, provenance, clear limitations, human approval points, and graceful failure states.

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

Choose the right home for state - URL, server, component, form, or shared client state - and implement caching, synchronization, optimistic interaction, and recovery with discipline.

Build and evolve a reusable design system and component platform in Storybook so teams can ship consistent, accessible experiences faster.

Ship and operate

Own delivery from local development through production across Azure, AWS, and Databricks Apps, selecting managed, serverless, or container-based approaches that fit the mission and security context.

Automate build, test, security, and deployment pipelines; use infrastructure as code, dependency and supply-chain controls, feature flags, progressive delivery, and repeatable environment promotion.

Instrument the browser and application with logs, metrics, traces, error reporting, product analytics, and Core Web Vitals so the team can see what users experience and act on it.

Create a balanced quality strategy spanning unit, component, contract, accessibility, visual, performance, and end-to-end tests. Treat production reliability and incident learning as part of product quality.

Lead and elevate

Set a forward-looking front-end roadmap, document architectural decisions, communicate tradeoffs, and keep the platform modern without chasing novelty for its own sake.

Partner directly with users and leaders, explain complex technical choices clearly, invite dissent, and create alignment across design, product, data, AI, security, and engineering.

Mentor engineers and designers, lead design and code reviews, establish front-end quality standards, and create a paved road that improves delivery across the team.

Use AI-assisted design and development tools responsibly to accelerate discovery, coding, testing, documentation, and analysis while preserving human review, security, traceability, and engineering judgment.

Measure outcomes, not output: adoption, task success, time on task, error rates, accessibility, performance, reliability, user confidence, and mission value.

This is a toolbox, not a trivia test. You do not need every library on this list. You do need deep React fundamentals, current hands-on expertise, and the judgment to choose - or reject - a technology for the right reasons.

Core React and language: React, Next.js App Router, React Server Components, Server Functions, React Compiler, TypeScript, JavaScript, Node.js, semantic HTML, modern CSS, browser APIs, Web Workers, and package management with pnpm.

UI and design systems: Tailwind CSS, shadcn/ui, Base UI, React Aria or Radix UI, design tokens, Storybook, Figma, Motion, container queries, responsive and adaptive design, progressive enhancement, and component-driven development.

Data, state, and forms: GraphQL, REST, OpenAPI, GraphQL Code Generator, TanStack Query, Zod, URL state, local React state, Zustand or Jotai when shared client state is justified, React Hook Form, WebSockets, Server-Sent Events, and streaming data patterns.

Data visualization and scale: TanStack Table and Virtual, D3, Observable Plot, Vega-Lite, Apache ECharts, Canvas, WebGL or WebGPU when the workload calls for it, plus performance budgets, virtualization, code splitting, and efficient rendering of large datasets.

AI experience engineering: Streaming model responses, RAG and agentic interactions, tool execution, source attribution and provenance, human-in-the-loop controls, feedback and evaluation workflows, transparent limitations, and resilient UX for latency, partial results, and model failure.

Quality and accessibility: Vitest, React Testing Library, Playwright, Mock Service Worker, Storybook interaction and visual testing, automated accessibility checks, keyboard and screen-reader validation, WCAG, Section 508, and performance profiling.

Cloud and operations: Git, CI/CD, Docker, Terraform, Bicep or cloud development kits, Azure, AWS, Databricks Apps, OAuth and OpenID Connect, role- and attribute-based access control, OpenTelemetry, centralized logs, metrics and traces, error tracking, feature flags, and product analytics.

5 or more years of professional front-end or product engineering experience, or equivalent evidence of senior-level impact, including ownership of production React applications.

Deep expertise in React, TypeScript, JavaScript, HTML, CSS, browser behavior, component architecture, rendering, accessibility, and front-end performance.

A record of taking products from vision through discovery, design, implementation, deployment, support, and iterative improvement - not only contributing isolated tickets.

Experience shipping applications used by thousands of users or more, with practical knowledge of rollout, telemetry, reliability, support, performance, and change management at scale.

A portfolio or case studies that show human-centered design thinking, personas and flows, prototypes, architectural decisions, shipped software, tradeoffs, and measurable outcomes.

Hands-on skill conducting user research and usability testing, synthesizing ambiguous findings, and translating them into coherent interaction models and product decisions.

Experience building data-heavy, API-driven applications and making disciplined choices about server state, client state, caching, forms, validation, real-time updates, and error recovery.

Experience building or contributing to accessible design systems, reusable component libraries, and shared front-end standards.

Experience deploying and operating modern web applications in at least one major cloud environment, with the ability to work across Azure, AWS, and Databricks Apps.

Strong written and verbal communication, technical leadership, curiosity, self-direction, and comfort making progress when the problem is not yet well defined.

Public Trust clearance, or the ability to obtain one.

Direct experience with Databricks Apps, Databricks SQL, Unity Catalog, model serving, lakehouse patterns, or governed data and AI applications.

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

Experience with biomedical, scientific, clinical, research, or public-health data; familiarity with FAIR data principles, FHIR, data provenance, or research data governance.

Advanced data visualization experience involving high-dimensional, graph, temporal, geospatial, or very large datasets.

Experience with Web Workers, WebAssembly, Canvas, WebGL, WebGPU, local-first or offline-capable applications, or other advanced browser capabilities.

Experience with product experimentation, feature flags, A/B testing, product analytics, and outcome-based product development.

Experience delivering into secure or regulated federal environments, including Section 508, zero-trust identity, privacy, auditability, and DevSecOps controls.

A history of raising the bar through technical strategy, mentoring, design-system leadership, open-source contribution, or front-end platform enablement.

Users can complete complex mission workflows faster, with fewer errors, less training, and greater confidence in the data and AI supporting their decisions.

The front-end platform becomes a force multiplier: reusable components, clear patterns, fast feedback, high-quality tests, and predictable deployments make the whole team more effective.

Applications are fast, accessible, secure, observable, reliable, and supportable across Azure, AWS, and Databricks Apps - not just impressive in a demo.

Production evidence and user feedback continuously shape the roadmap, and the team gets better at turning ambiguous mission needs into useful software.

The National Institutes of Health seeks fundamental knowledge about living systems and applies that knowledge to enhance health, lengthen life, and reduce illness and disability. Learn about the NIH mission.

NIH's current direction for data science emphasizes new opportunities in software, computational methods and artificial intelligence, along with a federated biomedical research data infrastructure. You will help turn those capabilities into usable mission experiences - interfaces that help people explore evidence, understand data, collaborate, and act with confidence. Explore the NIH Strategic Plan for Data Science.

GDIT is a global technology and professional services company that delivers technology solutions and mission services across the U.S. government, defense, and intelligence community. Our work spans artificial intelligence, cloud, cyber, software development, and the mission systems that help create a safer, smarter world.

That culture is backed by GDIT's Emerge innovation centers and technology labs, where teams collaborate with customers and technology partners to rapidly prototype, test, and validate mission solutions across AI, cloud, cyber, software development, high-performance computing, and other emerging technologies. The goal is not a demo. It is mission-ready software in users' hands.

The culture we are building on this team is high ownership, direct collaboration, fast learning, thoughtful tradeoffs, and the freedom to turn a strong idea into a working product. We want someone who brings an informed point of view, listens hard, changes their mind when the evidence changes, and cares deeply about the people using what they build.