Senior Software Engineer

Pearson•Hoboken, NJ

5d•Onsite

About The Position

Pearson Learning Studio is seeking a Senior Software Engineer to join the Re-imagining Assessments (REIA) squad within the PLS team to help design and build next-generation AI-powered learning experiences using Agentic AI frameworks and LLM-based architectures. This role is focused on developing intelligent, scalable AI systems with strong emphasis on Agentic workflows, LangGraph-based orchestration, state management, prompt engineering, and Retrieval-Augmented Generation (RAG). The ideal candidate will have deep experience building AI-driven applications using Python and modern AI orchestration frameworks.

Requirements

6–8 years of software engineering experience.
Strong hands-on experience with Python development.
Experience building AI/LLM-powered applications in production environments.
Hands-on experience with LangGraph, LangChain, or similar AI orchestration frameworks.
Strong understanding of Agentic AI concepts, workflow orchestration, and state management.
Experience implementing RAG pipelines, embeddings, and vector databases.
Strong prompt engineering skills and understanding of LLM behavior optimization.
Experience building scalable APIs and distributed systems.
Strong analytical, debugging, and problem-solving skills.
Excellent collaboration and communication skills.
Bachelor’s degree in Computer Science, Engineering, or related field.

Nice To Haves

Experience with OpenAI, Anthropic, or other enterprise LLM platforms.
Familiarity with AI observability, evaluation frameworks, and guardrails.
Exposure to AWS, Azure, or GCP cloud platforms.
Experience in EdTech or content-driven platforms.
Experience working within Agile product delivery teams.

Responsibilities

AI & Agentic System Development: Design and implement Agentic AI workflows using frameworks such as LangGraph and LangChain. Develop and manage multi-step AI orchestration pipelines with robust state management. Integrate and optimize Large Language Models (LLMs) for intelligent learning experiences. Design and implement RAG pipelines using embeddings and vector databases. Create, evaluate, and optimize prompts to improve response quality, reasoning, and reliability. Build scalable AI services and APIs using Python.
Platform & Engineering: Develop production-grade backend services and AI integration layers. Contribute to scalable system architecture, observability, and performance optimization. Collaborate with engineering and product teams to translate business requirements into AI-driven solutions. Troubleshoot and resolve production issues with ownership and urgency.
Agile Collaboration & Technical Leadership: Participate actively in Agile/Scrum ceremonies and technical planning sessions. Contribute to architecture reviews, technical design discussions, and engineering best practices. Mentor junior engineers and support team-wide technical growth.