Manager Software Engineering

PUBLICIS GROUPE•New York, NY

37d

About The Position

As a Staff Software Engineer, GenAI & Applied Innovation, you will be the senior handsâon engineer in a crossâfunctional Alphaâ¯Labs team. Your mandate: turn cuttingâedge generativeâAI research and dataâscience insights into live demonstrations that differentiates Publicis in competitive pitches and largeâscale client engagements. You will architect and build cloudânative services, GenAI-powered prototypes and intelligent APIs, then collaborate with data scientists, audience strategists, creatives and media technologists to embed those solutions across the connected consumer journey.

Requirements

6+â¯years professional softwareâengineering experience (or 4+â¯years with a relevant advanced degree).
Expertâlevel Python plus proficiency in at least one additional modern language (TypeScript/JavaScript, Java, Go, Dart, etc.).
Handsâon experience calling or fineâtuning GenAI/LLM APIs (e.g., GPTâ4o, Claude, Gemini) and integrating them into userâfacing or serviceâlayer applications.
Working knowledge of frontâend or mobile frameworks (React, Next.js, Flutter, etc.).
Prior work with AIâagent orchestration, vector databases (Pinecone, Weaviate, PGVector) or LangChain/LlamaIndex.
Experience deploying models or apps in Databricks and using MLflow or similar MLOps tooling.
Familiarity with marketingâtech or adâtech domains, including identity graphs, segmentation and measurement.
Thrives in fastâmoving, ambiguous environments; balances strategic vision with handsâon execution.

Responsibilities

Design, build and own backend services, microservices and cloud functions (AWS, Azure, Databricks) that power GenAI and data science workflows.
Integrate and experiment with GenAI APIs (OpenAI, Claude, proprietary LLMs) and agent/tool frameworks; implement retrieval augmented generation and vector database pipelines where useful.
Develop occasional cross platform front ends (React, Next.js, Flutter) to showcase prototypes and MVPs.
Rapid prototype novel audience intelligence or ad tech concepts for new business pitches; evolve proofs of concept into scalable products.
Collaborate with data scientists to operationalize predictive segmentation, targeting and measurement models.
Embed observability, monitoring and automated CI/CD so experiments can harden into production quickly.
Act as the technical lead within the squad: set coding standards, review PRs and mentor engineers.
Translate complex AI/ML ideas into clear narratives for creative, media and C suite audiences.
Contribute to hackathons, design thinking sprints and CoreAI product road mapping initiatives