Job Information
Pearson Senior Software Engineer - AI in Hoboken, New Jersey
Senior Software Engineer – Applied AI & Generative Systems
Pearson Learning Studio (PLS)
Role Overview
Pearson is accelerating the adoption of applied AI and generative technologies to power next-generation learning, assessment, and knowledge-driven experiences at global scale.
We are seeking a Staff AI Engineer to lead the design, standardization, and delivery of production-grade AI systems that are scalable, reusable, and enterprise-ready .
This is a senior individual contributor role with organization-wide impact . You will define architectural direction, establish engineering standards, and solve complex cross-domain challenges—enabling multiple teams to build high-quality, safe, and performant AI-powered products .
You will operate at the intersection of platform engineering, applied AI, and product innovation , turning cutting-edge capabilities into reliable, repeatable systems .
Key Responsibilities
Technical Leadership & Architecture
Define and evolve the reference architecture for applied AI and GenAI systems across the organization.
Establish reusable patterns, frameworks, and abstractions that accelerate development across teams.
Lead complex design decisions across scalability, latency, cost efficiency, and model performance .
Drive technical alignment through design reviews, RFCs, and architectural governance .
Serve as a technical north star for AI system design and engineering rigor.
Applied GenAI Systems (Core Focus)
Architect and build LLM-powered systems including:
Retrieval-Augmented Generation (RAG) pipelines
Multi-step reasoning workflows
Agentic systems and intelligent assistants
Design end-to-end AI pipelines spanning:
Data ingestion & transformation
Embeddings & indexing
Inference orchestration
Evaluation & feedback loops
Move AI solutions from prototype production scale , ensuring robustness and maintainability.
Optimize systems for latency, cost, and output quality at scale .
AI Platform & Reusability
Build shared AI capabilities and internal platforms consumed by multiple product teams.
Standardize tooling for:
Prompt/version management
Evaluation frameworks
Experimentation and A/B testing
Enable teams to safely and efficiently integrate AI without reinventing core infrastructure.
Content & Knowledge Intelligence
Design systems that enable AI to reason over large-scale structured and unstructured content .
Drive architecture for:
Content ingestion pipelines
Semantic enrichment and chunking strategies
Hybrid search (vector + keyword + metadata)
Ensure outputs are contextually accurate, explainable, and aligned with domain knowledge .
Reliability, Safety & Responsible AI
Embed responsible AI principles into system design (bias mitigation, guardrails, explainability).
Ensure compliance with enterprise standards for security, privacy, and governance .
Design for observability and resilience :
Model performance monitoring
Drift detection
Failure handling and fallback strategies
Proactively identify and mitigate risks related to hallucination, misuse, and data integrity .
Influence & Technical Mentorship
Act as a multiplier for engineering teams , unblocking complex technical challenges.
Mentor engineers on applied AI best practices, system design, and production readiness .
Partner with Product, Data Science, and Engineering leaders to turn ambiguous problems into scalable solutions .
Raise the engineering bar through clear documentation, code quality standards, and design excellence .
Required Qualifications
8–12+ years of software engineering experience, with deep hands-on work in applied AI / GenAI systems .
Proven track record of building and operating production-grade AI systems at scale .
Strong proficiency in Python and modern distributed/service-oriented architectures .
Deep expertise in:
Large Language Models (LLMs)
Retrieval techniques (RAG, hybrid search)
Embeddings and vector databases
Prompting strategies and evaluation methods
Experience deploying and operating systems in cloud environments (AWS, Azure, or GCP) .
Strong system design skills with cross-team technical influence .
Preferred Qualifications
Experience building internal AI platforms or shared services used across multiple teams.
Familiarity with agentic architectures and workflow orchestration frameworks .
Experience with ML/ LLMOps practices , including:
Monitoring and observability
Model/version lifecycle management
Evaluation pipelines
Exposure to education, knowledge systems, personalization, or assessment domains .
Experience with high-scale content systems or search platforms .
This is a hybrid work setup, where the candidate will be required to work three days onsite at our Hoboken office.
Applications will be accepted through April 27. 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 role is between $140,000 - $160,000
This position is eligible to participate in an annual incentive program, and information on benefits offered is here
Who we are:
At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates 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 are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.
Job: Engineering
Job Family: TECHNOLOGY
Organization: Higher Education
Schedule: FULL_TIME
Workplace Type: On-site
Req ID: 23659