Lead/Senior Full Stack AI Engineer

Company Description

Thought Industries powers the business of value with our industry-leading Learning Platform and AI-driven innovations. Founded in 2013, we believe customer learning should be modern, intuitive, engaging, and scalable. Our award-winning learning platform delivers personalized learning and measurable impact for global enterprises—and now, with our new Customer Value Realization AI Agents, we help organizations automate content creation, personalize experiences, and drive real-time customer value.

Job Description

A Senior/Lead AI Engineer is a hands-on engineering position that combines deep technical expertise with advanced AI tool proficiency to accelerate development and lead complex integration efforts within our Next.js/TypeScript codebase. This role requires someone who can leverage cutting-edge AI models and tools to architect and build sophisticated survey platform integrations (Medallia, SurveyMonkey, Typeform, etc.), design scalable job orchestration systems using Inngest, and create AI agents that effectively extract and analyze survey data into actionable insights. They will be a critical partner to our product team, aligning roadmaps and translating product goals into robust, well-architected solutions. They operate with a product-led growth mindset—building self-serve, instrumented experiences that drive activation, retention, and expansion.

This is a full-time position based in our Boston office, with a requirement to work onsite at least three (3) days per week as part of our hybrid work model. This role reports to the Director of Engineering.

Core Responsibilities

• Architect and implement survey platform integrations (Medallia, SurveyMonkey, Typeform, Qualtrics, etc.) using AI-assisted development.

• Design and build scalable job orchestration systems using Inngest for processing survey data, scheduling syncs, and managing complex workflows.

• Leverage AI tools (Cursor, Claude, etc.) to achieve 10x development productivity across the full stack.

• Build AI agents that extract, normalize, and analyze survey response data from multiple platforms into unified metrics and insights.

• Make technical decisions for data pipeline architecture, ensuring efficient processing of large-scale survey datasets.

• Engineer sophisticated prompts for extracting sentiment, themes, and actionable insights from unstructured survey responses.

• Implement robust error handling and retry mechanisms for job systems handling critical survey data synchronization.

• Contribute substantially to our Next.js/React codebase with a focus on server components and streaming UI patterns.

• Build and optimize serverless functions on Vercel for real-time survey data processing and webhook handling.

• Establish data quality standards and validation processes for survey integrations within your domain.

• Participate in code reviews with a focus on AI-assisted code quality, architecture, and performance.

• Collaborate with team members to share AI development techniques and prompt engineering strategies.

• Work with product teams to define technical requirements for new survey integrations and features.

• Monitor and optimize job performance, ensuring SLAs are met for data freshness and processing times.

• Stay current with survey platform APIs, job orchestration patterns, and AI advancements in data processing.

• Define and instrument PLG funnels (activation, retention, expansion) in collaboration with product and growth, using tools like PostHog.

• Ship self-serve onboarding and in-product guidance for integrations to reduce time-to-value.

Qualifications

• 8+ years of full-stack development experience with modern TypeScript/JavaScript frameworks.

• 2+ years of experience building and maintaining job orchestration systems (Inngest, Airflow, Temporal, Bull, etc.).

• Experience integrating with survey platforms (Medallia, SurveyMonkey, Typeform, Qualtrics) or similar third-party APIs at scale.

• 2+ years of hands-on experience using AI tools for software development (Cursor, Claude, ChatGPT, etc.) with demonstrated productivity gains.

• Experience operating in a PLG environment: instrumentation, experimentation, and optimizing activation/retention loops.