Company description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value. Overview 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. Qualifications 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. Additional information Set Yourself Apart With: Prior work on GenAI, CoPilot, or RAG-based systems. Familiarity with marketing data models and real-time customer journeys. Exposure to NLP, LLMs, and retrieval frameworks beyond the core requirements above. A Tip from the Hiring Manager: “AI is evolving fast – join us to work hands-on with big clients, sharpen your skills, and stay future-ready. Benefits of Working Here: Gender-Neutral Policy 18 paid holidays throughout the year. Generous parental leave and new parent transition program Flexible work arrangements Employee Assistance Programs to help you in wellness and well-being. 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.
