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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Fullstack Engineer - **Company:** Publicis Groupe - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $112,290.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Client Server Models, Cascading Style Sheets (CSS), Databases, Continuous Integration, Information Engineering, Data Synchronization, Data Visualization, Relational Databases, JSON, Python (Programming Language), Key Management, Machine Learning, Cloud Services, Next.js, SQL Databases, TypeScript, Web Applications, Web Application Frameworks, Data Logging, Network Routers, Google Cloud, Load Balancing, ReactJS, Caching, Generative AI, Backend, Fastapi, Build Management, Material UI, Machine Learning Operations, Front End Software Development, Restful APIs, Api Management, Databricks, Web Api - **Published:** July 2, 2026 - **Apply:** https://www.disabledperson.com/jobs/73451729-senior-fullstack-engineer ## About the Role * 6-8 years of building production internal or enterprise web applications * Strong front-end skills: React, TypeScript , modern component patterns (e.g. Next.js App Router, utility-first CSS, accessible component libraries) * Demonstrated back-end/API experience: Python and an async web framework ( i.e. FastAPI or equivalent) * Solid understanding of REST APIs, JSON contracts, and client/server error handling * Experience integrating UIs with backend job systems or long-running workflows (polling, status transitions, callbacks) * Comfort reading SQL-shaped data models and collaborating on relational-database-backed APIs * Ability to own features vertically (API + UI + release ) * Clear written and oral communication; experience working in Agile with data and engineering partners Preferred Q ualifications * Experience with cloud data platforms : job APIs, SQL warehouses, catalog-backed dimension and report tables ( i.e. AWS, Google Cloud, etc.) * Familiarity with ML/analytics product surfaces: model cards, run configuration, report types, export/download flows * Deep experience with s erver-state management, caching, and polling * Data visualization: charting libraries, maps, or custom tooltip and axis work for analytics UIs * Exposure to agent or tool API patterns on internal platforms * Experience with cloud-hosted deploys (containers, load balancers, secrets management) and CI/CD * Multi-tenant or client-context routing (e.g. request context * schema or catalog selection) * Experience with Databricks (jobs, deployment, UC, Genie, etc.) ## Description We are building an internal analytics and model operations platform that lets business and analytics users configure machine learning pipelines , trigger long-running data jobs, monitor execution, and explore results in rich visual reports. The stack pairs a modern web front end with a Python API service, a relational database, and cloud data platforms where models and pipelines run. This role leads delivery across the entire stack: user-facing flows, API contracts, job and report state management, and production hardening. You will work closely with data science, data engineering, and product to turn machine learning capabilities into reliable, intuitive experienc e . Team Culture & Collaboration You will build the application where analysts , business users and clients interact with and leverage machine learning models to drive real value and revenue . The work is full-stack, visible, and tied directly to client deliverables. The team brings together decades of experience in marketing and AdTech and are all motivated to develop the best platform to drive client growth and innovation. The group is genuinely excited to work on this platform, and there is a real opportunity to own the work and learn from other disciplines like data science, generative AI, marketing intelligence, audience intelligence, machine learning engineering, and more. Responsibilities User I nterface & E xperience * Design and build modern web applications for model configuration, job submission, and report exploration * Translate data science and analytics pipelines into clear, validated user flows (builders, wizards, configuration panels) * Implement dashboards, selection forms, and report visualizations (charts, flow diagrams, maps, comparison views) * Own form validation, cascading field behavior, and error states so users cannot submit jobs that will predictably fail * Ensure usability, responsiveness, and consistent patterns across different model and report types Backend APIs & D ata C ontracts * Extend Python API services with REST endpoints that expose curated data to the UI (dimension tables, report payloads, run configuration, exports) * Design JSON APIs that support efficient front-end consumption (filter metadata, report access by run identifier, enriched job status) * Collaborate on job orchestration flows: submission, execution logging, polling, callbacks, and navigation from run to report Application S tate, P erformance and R eliability * Manage client -side state and server synchronization for long-running jobs (in-progress reports, polling, retry, empty-data cases) * Establish and extend patterns for data fetching and caching to eliminate duplicate API calls and improve perceived performance * Harden edge cases: handles cases for no-data reports, manage parent/child job relationships, encoded path parameters, multi-audience exports, production release stability Platform I ntegration * Integrate UI and APIs with orchestration layers, job metadata, ingested dimension tables, and report export pipelines * Support agent or tool facing workflows where platform capabilities are exposed to downstream consumers via APIs * Lead CI/CD for the application and support release cadence for front-end and back-end services Cross-functional C ollaboration * Partner with data scientists to understand model parameters, defaults, and validation rules * Partner with data engineering on pipeline contracts, preflight checks, and data sync behavior * Break work into incremental deliverables (API first, then UI) and ship against product epics ## Related Videos - [GraphQL + Apollo + Next.js: A Lovely Trio](https://www.wearedevelopers.com/videos/311-graphql-apollo-next-js-a-lovely-trio) - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Build and Deploy a Fullstack App with Open Source Tooling](https://www.wearedevelopers.com/videos/775-build-and-deploy-a-fullstack-app-with-open-source-tooling) - [Create a Programmatic SEO Project Using Next.js and Static Site Generation](https://www.wearedevelopers.com/videos/449-create-a-programmatic-seo-project-using-next-js-and-static-site-generation) - [From Zero to Hero: NextJS 13 and Tailwind CSS for Beginners](https://www.wearedevelopers.com/videos/766-from-zero-to-hero-nextjs-13-and-tailwind-css-for-beginners) ## Related Articles - [The 7 Most Popular Backend Frameworks for Developers](https://www.wearedevelopers.com/magazine/403-the-7-most-popular-backend-frameworks-for-developers) - [16 Best Free React UI Libraries in 2025](https://www.wearedevelopers.com/magazine/148-16-best-free-react-ui-libraries-in-2025) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [What’s the Difference Between Frontend and Backend Development?](https://www.wearedevelopers.com/magazine/240-what-s-the-difference-between-frontend-and-backend-development) - [React Developer Salary [2023]](https://www.wearedevelopers.com/magazine/198-react-developer-salary-2023) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)