Lead Field AI Engineer for EdTech Deployments

Cengage Group; Manchester (NH); On-site; USD 117,000 - 187,000; Full time

Job summary

Cengage is seeking a Lead Field Development Engineer to embed with strategic institutional partners, architect, configure, and ship production-grade AI and platform solutions tailored to academic environments. You will own deployments, influence product roadmaps, mentor engineers, and set standards for complex institutional AI deployments.

You will write production code, drive LTI integrations, and partner with product, platform, and sales teams to deliver measurable outcomes across MindTap,

Qualifications

• 7+ years of software engineering experience in complex, customer-facing environments.
• 3+ years in a customer-embedded or field-facing engineering role such as FDE, Solutions Engineer, Applied AI Engineer, or Implementation Architect, with ownership of full deployments rather than demonstrations along
• Strong full-stack engineering skills, including Python, JavaScript/TypeScript, REST or GraphQL API design, and modern application frameworks
• Hands-on experience building and deploying LLM-based applications in production, including RAG pipelines, prompt engineering, tool-calling agents, and evaluation frameworks
• Demonstrated experience with LMS integration standards such such as LTI 1.3, LTI Advantage, AGS, NRPS, and Deep Linking
• Proficiency with cloud platforms; AWS is preferred, with experience across services such as Lambda, ECS or EKS, RDS or Aurora, S3, API Gateway, and CloudWatch
• Working knowledge of learning analytics standards such as xAPI or Caliper and educational data-privacy frameworks including FERPA, COPPA, and applicable state requirements

Responsibilities

• Embed with 3–5 strategic institutional accounts at a time, working directly with partners to understand instructional workflows, legacy LMS architectures, and institutional data environments before proposing a solution
• Lead end-to-end delivery of MindTap AI, WebAssign, Cengage Unlimited, and custom GenAI integrations from discovery through production launch and ongoing iteration
• Design and build institution-specific configurations including adaptive learning paths, RAG-backed course assistants, and auto-graded problem banks that address pedagogical challenges at scale
• Drive LTI 1.3 and LTI Advantage integrations between Cengage platforms and institutional LMS environments such as Canvas, Blackboard, D2L, and Moodle, including SSO, grade passback, and data flows
• Translate field-derived deployment patterns, integration heuristics, and failure modes into first-class contributions to Cengage's product and engineering roadmap
• Write production-quality code in Python, JavaScript/TypeScript, and SQL to build integration middleware, data pipelines, and custom tooling that extend Cengage's core platforms
• Architect and deploy agentic AI workflows using LLM APIs and retrieval-augmented generation pipelines grounded in institutional course content
• Build and maintain automated evaluation frameworks that measure the accuracy, safety, and pedagogical quality of AI-generated student guidance at the institution level
• Ensure deployments meet FERPA, WCAG 2.1 AA accessibility, institutional data-governance requirements, and Cengage's AI safety standards
• Present deployment architecture, outcomes data, and AI safety posture to institutional CIOs, Chief Academic Officers, and VP-level stakeholders with authority and clarity
• Define adoption milestones and renewal-driving outcomes for strategic accounts, ensuring technical delivery translates into measurable institutional value

Skills

Python

JavaScript/TypeScript

REST/GraphQL

LLM deployments

LTI integrations

AWS

FERPA compliance

Education

Graduate degree in Computer Science, Data Science, Educational Technology, or related field

AWS Certified Solutions Architect

Tools

LTI 1.3

LTI Advantage

AWS Lambda/ECS/EKS

RDS/Aurora

S3

API Gateway

Job description

Cengage is seeking a Lead Field Development Engineer to embed with strategic institutional partners, architect, configure, and ship production-grade AI and platform solutions tailored to academic environments. You will own deployments, influence product roadmaps, mentor engineers, and set standards for complex institutional AI deployments.

You will write production code, drive LTI integrations, and partner with product, platform, and sales teams to deliver measurable outcomes across MindTap,