Pearson

Senior Software Engineer

Pearson$130K — $150K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 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.
  • 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.

Responsibilities

  • 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.
  • Develop production-grade backend services and AI integration layers.

Benefits

  • Hybrid workplace model for flexibility.
  • Incentive program participation opportunity.
  • Career development and mentoring programs.
  • Collaborative and hands-on Agile environment.
  • Focus on next-generation educational technology solutions.
Full Job Description
Senior Software Engineer - AI/Agentic Systems

Pearson Learning Studio (PLS) - REIA Squad | Hoboken, NJ

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.

Key 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.

Required Qualifications
  • 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.

Preferred Qualifications
  • 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.

Applications will be accepted through September 11. This window may be extended depending on business needs.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows:

The full-time salary range for this position is between $130,000 - $150,000 Annually.

This position is eligible to participate in an annual incentive program, and information on benefits offered is here .

Job: Engineering

Job Family: TECHNOLOGY

Organization: Higher Education

Schedule: FULL_TIME

Workplace Type: Hybrid

Req ID: 25699

About Pearson

Pearson is a publishing and education company that provides educational materials, learning technologies, and assessments to schools, universities, and professional organizations. The company's products and services include textbooks, online learning platforms, and certification exams. Pearson's customers include the University of Phoenix, the British Council, and the Association of Chartered Certified Accountants.
Learn more about Pearson
Size
20,744 employees
Market Cap
$8.1 billion
Industry
Net Income
$265 million
Founded
1997
5 Year Trend
-5.5%
Revenue
$3.5 billion
NASDAQ

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