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Principal Architect, CPQ

📅 Jul 23
LLM EngineeringAgentic SystemsRAGPrompt Engineering
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📜 Description

  • Design a hyperscaler- and LLM-agnostic product that runs on customer infrastructure.
  • Build the semantic data core with graph-based modeling, typed relationships, tenant isolation, and provenance.
  • Architect agentic services, including tool-using LLM agents, orchestration, guardrails, and retrieval grounding.
  • Set standards for async APIs, state machines, code generation, and draft-to-active data lifecycles.
  • Lead technical delivery, mentor engineers, and make build-versus-buy and model-selection decisions.

🛠️ Requirements

  • 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).

✨ Benefits

  • Own the end-to-end architecture and technical vision for an AI-native CPQ platform.
Full job description
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.
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