Principal Architect, Systems & AI

EnvisionWare, Inc.

22h

About The Position

EnvisionWare is hiring a Principal Architect, Systems & AI to serve as the technical truth layer for a company-wide AI-first transformation. You will own architectural integrity across a portfolio of 40+ products, use AI to map and interrogate the existing codebase, and validate every AI-generated technical claim before it becomes a decision. This role is the guardrail that makes speed safe. You report into the Director of Engineering and act as architecture authority across the internal team and Contour pod. Contract-to-hire is acceptable if that is the fastest path to the right person. The right candidate has deep systems-thinking capability, practical skepticism about both legacy systems and AI-generated output, and a track record of working close to delivery — not detached from it. EnvisionWare was formed almost 20 years ago with a single purpose – to create innovative, self-service and efficiency solutions that enhance library services and empower patrons. This mission continues to be the driving focus of EnvisionWare today, backed by a commitment to ensure that every library, regardless of size, receives the highest level of customer service and support. EnvisionWare is an equal opportunity employer, we recruit, hire, train, promote and provide all other privileges of employment to qualified people without regard to age, race, color, creed, national origin, gender, gender identity, gender expression, disability, marital status, veteran status, citizenship status, ethnicity, familial status, religion, sexual orientation or any other classification for which discrimination is prohibited.

Requirements

10+ years of architecture experience in messy, real-world production environments
Legacy modernization expertise — strangler patterns, characterization tests, and the judgment to know when rewrite is justified and when it isn't
Multi-stack knowledge: Java, Angular, .NET, PostgreSQL, Kubernetes (or comparable breadth)
Ability to understand unfamiliar code quickly and challenge weak assumptions — whether from humans or AI
Practical skepticism: you use AI aggressively but trust it only after validation
Comfort working close to delivery, code, and teams rather than operating as a detached enterprise architect

Responsibilities

Own architectural integrity across all products and major technical changes
Act as the architecture approval gate: every design touching system boundaries, auth, payment, or data models requires your sign-off
Perform system mapping, dependency analysis, and risk discovery — accelerated by AI but validated by you
Define the modernization roadmap: deciding where to stabilize, modularize, retire, or selectively rewrite
Establish technical guardrails that make AI-assisted development safe at scale
Use AI to crawl and map unfamiliar codebases, generate dependency views, surface hidden risks, and draft architecture proposals
Validate every AI-generated technical finding, treating it as a hypothesis until validated
Set the rules for what AI-generated work requires deeper human review — and enforce them
Run an AI-assisted codebase crawl and produce validated system maps and dependency views (First 90 Days)
Classify the portfolio: stabilize, modularize, modernize, retire, or selectively rewrite (First 90 Days)
Define architecture approval rules for cross-boundary changes (First 90 Days)
Validate any AI-generated technical findings before they appear in leadership or roadmap decisions (First 90 Days)
Set the technical guardrails that make AI maturity safe and achievable (First 90 Days)