Senior Fullstack Engineer

Publicis Groupe Holdings B.V; New York (NY); On-site; USD 100,000 - 135,000; Full time

Job summary

Publicis Groupe Holdings B.V in New York is searching for a full-stack developer to lead the delivery of an analytics platform. This role encompasses designing modern web applications and enhancing Python API services while collaborating closely with data science and engineering teams. The ideal candidate should have strong front-end skills in React and TypeScript, as well as backend experience using Python.

The company fosters a collaborative culture aimed at driving client growth through innovative solutions in machine learning.

Qualifications

• 6-8 years of building production internal or enterprise web applications.
• Strong front-end skills including React and modern component patterns.
• Demonstrated backend/API experience using Python and an async web framework.
• Solid understanding of REST APIs and JSON contracts.
• Experience integrating UIs with backend job systems or long-running workflows.

Responsibilities

• Design and build modern web applications for model configuration and report exploration.
• Extend Python API services with REST endpoints for UI consumption.
• Manage client-side state and server synchronization for long-running jobs.
• Integrate UI and APIs with orchestration layers and job metadata.
• Break work into incremental deliverables and ship against product epics.

Skills

React

TypeScript

Python

REST APIs

SQL

FastAPI

Job description

Overview

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 experience.

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 Interface & Experience

• 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 & Data Contracts

• 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 State, Performance and Reliability

• 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 Integration

• 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 Collaboration

• 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

Qualifications

• 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 (e.g. 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 Qualifications

• Experience with cloud data platforms: job APIs, SQL warehouses, catalog-backed dimension and report tables (e.g. AWS, Google Cloud, etc.)
• Familiarity with ML/analytics product surfaces: model cards, run configuration, report types, export/download flows
• Deep experience with server‑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