Senior AI Platform Engineer - GenAI, LLMs & MLOps

Pearson; Jefferson City (MO); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Annual incentive program

Job summary

Pearson is seeking a senior AI Platform Engineer to lead production AI capabilities across learner intelligence, personalization, and knowledge graphs. You will design, deploy, and operate AI services powering Pearson products in a cloud environment, with a focus on scalable MLOps and responsible AI practices.

You will collaborate with cross-functional teams including Product, Engineering, and Data Science to deliver measurable business impact and ensure governance, reliability, and cost

Qualifications

• 5+ years of experience building and deploying production AI/ML systems.
• Strong experience with applied machine learning, Generative AI, LLMs, RAG architectures, knowledge graphs, or agentic AI solutions.
• Hands-on experience building and deploying AI applications using foundation models and modern AI frameworks.
• Proficiency in Python and modern software engineering practices, including APIs, testing, CI/CD, version control, and production operations.
• Experience designing scalable AI platforms, services, and deployment architectures in AWS or similar cloud environments.
• Experience with containerization, orchestration, infrastructure-as-code, and production-grade deployment practices.
• Experience evaluating, monitoring, and optimizing AI systems for quality, reliability, safety, latency, scalability, and cost.
• Experience with modern AI technologies such as OpenAI, Anthropic, Bedrock, Azure OpenAI, LangGraph, LangChain, Semantic Kernel, vector databases, or similar platforms.
• Strong collaboration and communication skills with product, engineering, and business stakeholders.
• Bachelor's degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience.

Responsibilities

• Lead the design, development, deployment, and operation of production AI capabilities.
• Design and deliver Generative AI, LLM, RAG, and agentic AI solutions that create measurable impact.
• Build reusable AI platform capabilities, services, APIs, and workflows for Pearson products.
• Own the end-to-end AI delivery lifecycle from experiment to production and improvement.
• Establish scalable MLOps and AIOps practices for training, deployment, observability, governance, reliability, and cost.
• Partner with Product, Engineering, Design, Learning Science, and Data Science teams to identify opportunities.
• Evaluate emerging AI technologies and architectures balancing quality, safety, latency, and cost.
• Establish best practices for responsible AI, model evaluation, prompt engineering, and governance.
• Mentor engineers and data scientists to elevate AI engineering capabilities across Pearson.
• Communicate technical strategy, architecture decisions, trade-offs, risks, and outcomes to stakeholders across the business.

Skills

Python

MLOps

AWS

LLMs

RAG

Knowledge graphs

Generative AI

APIs

CI/CD

Docker

Kubernetes

IaC

OpenAI

LangChain

Vector databases

Terraform

Git

Education

Bachelor's degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience

Tools

Docker

Kubernetes

Terraform

Git

CI/CD tooling

Job description

Pearson is seeking a senior AI Platform Engineer to lead production AI capabilities across learner intelligence, personalization, and knowledge graphs. You will design, deploy, and operate AI services powering Pearson products in a cloud environment, with a focus on scalable MLOps and responsible AI practices.

You will collaborate with cross-functional teams including Product, Engineering, and Data Science to deliver measurable business impact and ensure governance, reliability, and cost