Principal AI Systems Architect

Sapience AI Corporation•Seattle, WA

5d•$204,000 - $216,000

About The Position

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. This is the most senior individual-contributor architecture role at Sapience AI. You own how the whole system fits together: how the KO graph, the COGENT architecture, the models, the serving layer, and the product surface combine into one coherent, scalable, trustworthy platform. You work across every part of the stack, setting the architectural direction that lets specialized teams build fast without the system pulling apart at the seams. You are a force multiplier: not the owner of one area, but the person who makes sure all the areas add up to a platform that can carry Sapience AI’s ambitions for years. Collective intelligence spans hard subsystems: knowledge, reasoning, models, serving, and experience. Each can be strong on its own and still fail as a whole if the architecture does not hold together. As the platform and the team grow, the cost of architectural drift compounds. Someone has to own the coherence of the system, the big technical bets, and the seams between teams. The Principal AI Systems Architect owns that. You set cross-cutting direction, make the hard architectural calls, and keep MINERVA and COGENT coherent, scalable, and trustworthy as they grow. You set the architecture for an AI platform and use AI to reason about it, to explore designs, stress-test trade-offs, and move faster, while holding the judgment that architecture at this level demands. The standard is human in partnership: AI accelerates the work, you own the judgment, the interpretation, and the call. The people who create the most value here are not the ones producing the most output. They are the ones turning evidence into clear, durable decisions.

Requirements

Extensive experience as a senior or principal engineer or architect on complex production systems.
Deep experience architecting AI or ML platforms end to end.
A track record of architecture that scaled with a growing product and team.
Strong systems, distributed systems, and data fundamentals.
Sound judgment on security, reliability, and trust at the architecture level.
The ability to lead through influence across many teams.
Hands-on credibility that senior engineers respect.
Distributed systems, data platforms, and ML infrastructure at an architectural level.
LLM, retrieval, vector, and graph systems.
Cloud platforms (AWS, GCP, or Azure), containers, and orchestration.
Observability, security, and reliability tooling.
Architecture and design tooling for complex systems.
Enough hands-on coding to prototype and prove out hard parts.
Deep architectural ownership of the MINERVA platform, KO graph, and COGENT architecture.
Prior principal engineer or architect roles on large-scale AI or software systems.
Experience carrying an architecture through significant growth.
A track record of cross-team technical leadership.
Experience in AI-native systems is strongly preferred.

Nice To Haves

Experience with knowledge graphs, neuro-symbolic systems, retrieval, or agentic AI.
Experience owning inference and infrastructure at scale.
Experience in trust-sensitive or regulated domains.
A record of setting standards that lifted an organization.
Experience integrating frontier advances into production architecture.

Responsibilities

Own how the KO graph, COGENT, models, serving, and product surface fit into one coherent system.
Set the cross-cutting architecture that lets teams build fast without drift.
Own the seams between subsystems, where the hardest problems live.
Make the architecture-level decisions that shape the platform for years.
Weigh build, buy, and bet choices with a clear point of view.
Keep the architecture aligned with where AI and the business are heading.
Design for scale, reliability, and trust as properties of the architecture, not add-ons.
Anticipate where the system will strain next and get ahead of it.
Make security and governance structural.
Set the standards and patterns that raise quality across the organization.
Reduce accidental complexity and duplicated effort across teams.
Make the right way the easy way.
Align specialized teams around shared architecture and interfaces.
Resolve the hardest cross-team technical questions.
Multiply the impact of every team through better structure.
Evaluate frontier advances and decide how they fit the architecture.
Separate durable direction from passing trends.
Bring in what matters without destabilizing the system.
Raise the technical judgment of senior engineers across the organization.
Model rigor, clarity, and honesty about trade-offs.
Help the whole organization make better architectural decisions.