Senior Software Engineer - Applied AI & Generative Systems

Role Overview

Pearson is at the forefront of integrating applied AI and generative technologies to transform the learning landscape on a global scale. We invite you to join us as a Senior Software Engineer, where you will take charge of designing, standardizing, and delivering production-grade AI systems that are scalable, reusable, and enterprise-ready. This role offers a unique opportunity to make a significant impact across the entire organization. You will play a pivotal role in setting architectural standards, establishing engineering excellence, and tackling complex cross-domain issues—enabling capable teams to deliver high-quality, safe, and efficient AI-powered products. Your responsibilities will bridge platform engineering, applied AI, and product innovation, converting state-of-the-art technologies into reliable, repeatable systems.

Key Responsibilities

Technical Leadership & Architecture

• Define and refine the reference architecture for applied AI and GenAI systems across the organization.
• Develop reusable patterns, frameworks, and abstractions to expedite development for teams.
• Lead in making critical design choices related to scalability, latency, cost efficiency, and model performance.
• Facilitate technical alignment through design reviews, RFCs, and architectural governance.
• Act as the technical north star for AI system design and engineering standards.

Applied GenAI Systems (Core Focus)

• Architect and develop LLM-powered systems including:
  • Retrieval-Augmented Generation (RAG) pipelines
  • Multi-step reasoning workflows
  • Agentic systems and intelligent assistants
• Design end-to-end AI pipelines that encompass:
  • Data ingestion & transformation
  • Embeddings & indexing
  • Inference orchestration
  • Evaluation & feedback mechanisms
• Transition AI solutions from prototype to production scale, ensuring robustness and maintainability.
• Optimize systems focused on latency, cost, and output quality at scale.

AI Platform & Reusability

• Construct shared AI capabilities and internal platforms utilized by multiple product teams.
• Standardize tools for:
  • Prompt/version management
  • Evaluation frameworks
  • Experimentation and A/B testing
• Empower teams to safely and efficiently integrate AI without duplicating core infrastructure.

Content & Knowledge Intelligence

• Design systems that allow AI to analyze large-scale structured and unstructured content.
• Drive architecture for:
  • Content ingestion pipelines
  • Semantic enrichment and chunking strategies
  • Hybrid search methodologies (vector + keyword + metadata)
• Ensure that outputs are contextually accurate, explainable, and aligned with domain knowledge.

Reliability, Safety & Responsible AI

• Incorporate responsible AI principles into system design (addressing bias, establishing guardrails, ensuring explainability).
• Guarantee compliance with enterprise standards for security, privacy, and governance.
• Design for observability and resilience by implementing:
  • Monitoring model performance
  • Detecting drift
  • Creating failure handling and fallback strategies
• Proactively identifying and mitigating risks associated with hallucination, misuse, and data integrity.

Influence & Technical Mentorship

• Serve as a catalyst for engineering teams, helping them navigate complex technical challenges.
• Guide engineers on applied AI best practices, system design, and production readiness.
• Collaborate with Product, Data Science, and Engineering leaders to transform ambiguous problems into scalable solutions.
• Elevate engineering standards through clear documentation, code quality, and design excellence.

Required Qualifications

• 8-12+ years of experience in software engineering with substantial hands-on involvement in applied AI / GenAI systems.
• Demonstrated ability to build and support production-grade AI systems at scale.
• Extensive proficiency in Python and modern distributed/service-oriented architectures.
• Strong expertise in:
  • Large Language Models (LLMs)
  • Retrieval techniques (RAG, hybrid search)
  • Embeddings and vector databases
  • Prompting strategies and evaluation methods
• Experience deploying and managing systems in cloud environments (AWS, Azure, or GCP).
• Excellent system design capabilities with experience influencing cross-team technical standards.

Preferred Qualifications

• Experience developing internal AI platforms or shared services that are utilized by various teams.
• Familiarity with agentic architectures and workflow orchestration frameworks.
• Background in ML/LLMOps practices, encompassing:
  • Monitoring and observability
  • Model/version lifecycle management
  • Evaluation pipelines
• Knowledge of education, knowledge systems, personalization, or assessment domains.
• Experience with large-scale content systems or search platforms.

This position follows a hybrid work model, with the expectation of three days onsite in our Hoboken office. Applications will be accepted through April 27. This window may be extended based on business needs.

Compensation at Pearson reflects a variety of factors, including skill set, experience, and specific location. As mandated by laws in various states, the pay range for this role is as follows: The full-time salary range for this position is between $140,000 - $160,000. This role is eligible for an annual incentive program, and additional details about benefits offered are available.

Who we are:

At Pearson, our mission is straightforward: to empower individuals to achieve their aspirations through learning. We view each learning opportunity as a stepping stone for personal growth. As the world's lifelong learning company, learning is not just what we do—it defines who we are. To learn more about us, visit our website. Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are made based on qualifications, merit, and business requirements. Qualified candidates will be considered regardless of race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status, or any other legally protected category. We actively seek qualified applicants who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. If you are an individual with a disability and require assistance or special accommodations to access our career site, please reach out via email for reasonable accommodations.