Senior Software Engineer - AI

Pearson•Hoboken, NJ

18h•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.
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.
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.

Benefits

This position is eligible to participate in an annual incentive program, and information on benefits offered is here [https://nam02.safelinks.protection.outlook.com/?url=https://pearsonbenefitsus.com/&data=04|01|[email protected]|2c256513c79f4679be7c08d9e7287ebb|8cc434d797d047d3b5c514fe0e33e34b|0|0|637794983376381246|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0=|3000&sdata=t1YQPUL7BgoclUd7yE2i86QAirLf4z3z8OEWgr42q7c=&reserved=0]

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