Senior Associate Technology L2 | PYTHON

Publicis Sapient is looking for Python Developers to join our team of bright thinkers and enablers. You will use your problem-solving skills, craft, and creativity to design and develop infrastructure interfaces for complex business applications. You will build and orchestrate agentic, GenAI-powered workflows that transform how our clients operate – from data ingestion and enrichment to intelligent, LLM-driven automation. We are on a mission to transform the world, and you will be instrumental in shaping how we do it with your ideas, thoughts, and solutions.

Your Impact:

Build and orchestrate agentic workflows using LangChain and LangGraph to power scalable, production-ready GenAI solutions.

Develop reusable components for data ingestion, transformation, enrichment, and validation that accelerate delivery across projects.

Ensure reliability, scalability, and traceability across agent workflows to support dependable, enterprise-grade AI applications.

Implement performance monitoring with tools like LangSmith and apply tuning mechanisms to continuously improve agent accuracy and efficiency.

Deploy and maintain Python-based GenAI services in production, leveraging Bitbucket, Git, and CI/CD tools for reliable releases.

Architect secure API communication and access management, using JWT, OAuth, and RBAC, to safeguard sensitive client data.

Apply NLP, LLM, and retrieval techniques, including vector stores and embeddings, to build context-aware, intelligent solutions for clients.

Your Skills & Experience:

Strong Python fundamentals (OOP, data structures, error handling) with hands-on experience using Pandas, NumPy, PySpark, or Dask.

Hands-on experience with LangChain, LangGraph, and Semantic Kernel, building agent orchestration, memory, and tool-use workflows.

Proficiency in Python API frameworks (Flask/FastAPI), with experience using IDEs such as VSCode and PyCharm.

Working knowledge of SQL/NoSQL databases, time-series data, and data modeling and schema design.

Basic integration experience with TensorFlow or PyTorch, plus exposure to vector databases (e.g., FAISS, Chroma) and embedding-based retrieval.

Proficiency with AWS Cloud Services and production deployment practices, including Bitbucket, Git, and CI/CD tools.

Strong understanding of security & access management – JWT, OAuth, RBAC – and secure API communication.