Senior Full Stack AI Engineer

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 We are seeking a Senior Full-Stack AI Engineer to build and scale enterprise-grade AI applications, agents, copilots, and workflow automation solutions. This role is focused on building and scaling enterprise AI solutions As a Senior Full-Stack AI Engineer, you will play a key role in building intelligent, scalable applications that move beyond AI experimentation into real business impact. You will work at the intersection of software engineering and applied AI, contributing to solutions that are production-ready, enterprise-grade, and aligned to our mission to Build what matters. Responsibilities Your Impact Design, develop, and deploy AI-powered applications using Python and modern AI frameworks. Build and optimize LLM orchestration workflows using LangChain and/or LangGraph. Translate business requirements into scalable, production-ready AI solutions. Develop and integrate REST APIs, microservices, and backend services supporting AI use cases. Collaborate with data scientists, product managers, and engineers to deliver end-to-end solutions. Contribute to architecture design decisions and implement best practices in software engineering and AI development. Ensure code quality, performance, and scalability through testing, debugging, and optimization. Stay current with advancements in Generative AI, LLM ecosystems, and emerging tooling. Qualifications Skills & Experience Bachelor’s degree in Computer Science, Engineering, or related field. 6+ years of experience in software development with strong Python expertise. Hands-on experience building applications using LangChain and/or LangGraph. Solid understanding of LLMs, prompt engineering, embeddings, and vector databases. Experience with API development, microservices architectures, and backend frameworks (e.g., FastAPI, Flask). Strong knowledge of software engineering principles, version control (Git), and CI/CD practices. Experience working in Agile environments and collaborating with distributed teams. Set Yourself Apart With Experience designing agentic workflows and advanced LLM orchestration patterns. Exposure to enterprise-scale AI implementations or client-facing delivery environments. Familiarity with cloud platforms (AWS, Azure, or GCP) for deploying AI applications. Strong system design and problem-solving skills with the ability to translate complexity into scalable solutions. Proven ability to communicate effectively with technical and non-technical stakeholders. Continuous learning mindset and passion for building real-world AI solutions that drive impact. Additional information An inclusive workplace that promotes diversity and collaboration. Access to ongoing learning and development opportunities. Competitive compensation and benefits package. Flexibility to support work-life balance. Comprehensive health benefits for you and your family. Wellness program and employee assistance. As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at [email protected]

Skills & Experience Bachelor’s degree in Computer Science, Engineering, or related field. 6+ years of experience in software development with strong Python expertise. Hands-on experience building applications using LangChain and/or LangGraph. Solid understanding of LLMs, prompt engineering, embeddings, and vector databases. Experience with API development, microservices architectures, and backend frameworks (e.g., FastAPI, Flask). Strong knowledge of software engineering principles, version control (Git), and CI/CD practices. Experience working in Agile environments and collaborating with distributed teams. Set Yourself Apart With Experience designing agentic workflows and advanced LLM orchestration patterns. Exposure to enterprise-scale AI implementations or client-facing delivery environments. Familiarity with cloud platforms (AWS, Azure, or GCP) for deploying AI applications. Strong system design and problem-solving skills with the ability to translate complexity into scalable solutions. Proven ability to communicate effectively with technical and non-technical stakeholders. Continuous learning mindset and passion for building real-world AI solutions that drive impact.

Your Impact Design, develop, and deploy AI-powered applications using Python and modern AI frameworks. Build and optimize LLM orchestration workflows using LangChain and/or LangGraph. Translate business requirements into scalable, production-ready AI solutions. Develop and integrate REST APIs, microservices, and backend services supporting AI use cases. Collaborate with data scientists, product managers, and engineers to deliver end-to-end solutions. Contribute to architecture design decisions and implement best practices in software engineering and AI development. Ensure code quality, performance, and scalability through testing, debugging, and optimization. Stay current with advancements in Generative AI, LLM ecosystems, and emerging tooling.