Aimed at senior architects with deep LLM engineering expertise who thrive in hands-on leadership roles building AI-native platforms from scratch.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Brillio 2 via Lever
Principal Architect - CPQ product will own the end-to-end architecture of an AI-native platform built on frontier AI models and agentic workflows. Define the technical vision across product architecture, data platforms, pricing engines, knowledge systems, and AI services while making critical build-vs-buy, platform, and model strategy decisions. Partner closely with product, engineering, and business stakeholders to create a scalable, enterprise-grade solution that transforms complex sales and pricing processes through automation and intelligence. This is a hands-on leadership role requiring deep technical expertise, architectural rigor, and the ability to attract and mentor high-caliber engineering talent.
What will you own?:
- Define the architecture for a hyperscaler and LLM-agnostic product built to run on customer infrastructure - not a platform-locked implementation.
- Design the semantic data core: graph-based modeling with typed relationships, multi-tenant isolation, and provenance.
- Architect agentic services - tool-using LLM agents, orchestration, guardrails, and retrieval grounding - as first-class product capabilities.
- Set standards for async API design, state machines, code generation/templating, and draft-to-active data lifecycles.
- Lead technical delivery end-to-end, mentor engineers, and make the build-vs-buy and model-selection calls.
Must-Have Experience::
- 15+ years building software, with a proven record of shipping real products 0-to-1 through scale - not just running projects.
- Core LLM engineering: designing agentic systems with frontier models (Claude / GPT) - tool / function calling, agent skills, multi-step orchestration, and memory.
- Production RAG: embeddings, vector search, chunking and re-ranking, semantic field-mapping, and grounding model output over enterprise data.
- Prompt & context engineering: structured / JSON output, schema validation, evals and regression harnesses, guardrails, and cost / latency / quality trade-offs.
- Strong in Python and modern JS/TS (React / Vite); async services, graph / semantic data modeling, containers, and cloud (Azure / AWS / GCP).
Nice to Have::
- CPQ / quote-to-cash or enterprise SaaS exposure. Salesforce or Revenue Cloud familiarity is a plus, not a requirement - this is a non-Salesforce-native product.
Candidates should demonstrate the below listed critical leadership qualities::
- Customer Advocacy - Ensures customer success on stated and unstated business priorities through strategic advice and market leading solutions.
- Owner’s Mindset - Is passionate about Brillio’s business, deeply committed to its success and makes decisions that are in the best interest of the firm.
- Innovation Ethos - Embraces ambiguity and adopts relentless experimentation to challenge current practices and enable continuous growth.
- Execution with Pace - Displays agility to deliver high quality results in the face of changing stakeholder expectations.
- Big Picture Thinking - Creates a common definition of shared success and sets bold targets that inspire the team towards new horizons.
- Winning Through Teams - Enables a culture of collaboration and empowers teams to "raise their game” to create a winning formula.
Source: Brillio 2 careers (Lever)