Principal AI Architect
Who We Are:
Discuss stands as an all-in-one qualitative research platform, driving next gen human centricity. We believe in the transformative impact of truly listening, understanding, and valuing customers' experiences, recognizing their critical role in fostering empathy. Trusted by the leading Market Insights, CX, and UX professionals worldwide, Discuss goes beyond data points, delivering in-depth insights in real time and transforming consumer relationships.
Our rapid growth and innovative AI-driven roadmap have positioned us as industry leaders, recognized by G2 for our speed and creativity in scaling qualitative research.
At Discuss, we are a team of curious, collaborative, and empathetic professionals dedicated to tackling fun, challenging problems. We offer the freedom to grow, lead, and innovate within an environment that values independence, flexibility, and personal and professional development.
Who We’re Looking For:
We are seeking a Principal AI Architect to own the evolution of our market research platform. Your goal is twofold: architecting sophisticated, privacy-first AI features for our global clients and leading the charge in transforming our internal development lifecycle through AI-augmented engineering.
The ideal candidate will bring deep expertise in AI/LLM implementation and full-stack architecture, with a strong focus on building privacy-first, scalable AI features. You will own both external product innovation and internal engineering transformation through AI-augmented development practices.
You thrive in complex environments, balancing performance, cost, and accuracy while designing intelligent systems. You’re also passionate about mentoring teams, driving adoption of emerging AI tools, and embedding best practices across the engineering organization.
In a perfect world, you’ll bring experience with distributed systems, real-time data processing, and AI infrastructure, along with familiarity in market research or analytics platforms.
What You’ll Do With Us:
AI Strategy & Orchestration
- Architect Complex Workflows: Design and implement multi-agent systems and LLM orchestration layers using frameworks like LangChain, LangGraph, or custom Node.js patterns.
- Performance Optimization: Implement advanced RAG (Retrieval-Augmented Generation) patterns, prompt caching, and model routing to balance cost, latency, and accuracy.
- Privacy & Compliance: Ensure all AI features adhere to market research privacy standards (GDPR, CCPA), focusing on PII redaction and secure data handling within LLM contexts.
Technical Leadership (Hands-on)
- Full-Stack Excellence: Lead the implementation of AI-driven UI components in React and scalable back-end services in Node.js (TypeScript).
- Infrastructure: Guide the selection of vector databases, embedding models, and monitoring tools (e.g., LangSmith, Helicone) to ensure system observability.
Engineering Acceleration
- AI for Engineering: Serve as the internal champion for AI-assisted development. Curate and implement toolsets (GitHub Copilot, Cursor, automated PR agents) to measurably accelerate our software delivery lifecycle.
- Mentorship: Upskill the broader engineering team on AI best practices, prompt engineering for devs, and the nuances of non-deterministic code.
What You’ve Done Before:
Required
- 8+ years of progressive software engineering experience
- 2+ years of hands-on experience with AI/LLM implementation
- Expert-level proficiency in Node.js/TypeScript and React
- Deep experience with OpenAI/Anthropic APIs, vector databases (Pinecone, Weaviate, or pgvector), and orchestration libraries
- Proven track record of designing distributed systems, microservices, and real-time data streaming
- Familiarity with data anonymization techniques and compliance frameworks within a cloud environment (AWS/Azure/GCP)
Bonus Points
- Experience with Python-based data pipelines
- Background in fine-tuning open-source models (e.g., Llama, Mistral)
- Experience with AI observability tools (LangSmith, Helicone)
- Familiarity with market research, analytics, or data platforms