Sr/Distinguished Architect, Continuous Quality & Release Engineering

Burtch Works; United States; Remote; USD 200,000 - 260,000; Full time

Job summary

Burtch Works client seeks a senior engineer to define and build a change-safety architecture for enterprise-scale software. You will design assurance plans, drive AI-assisted testing, and influence Reliability, Platform, Applications, AI, SecOps and Services teams.

You will own end-to-end release and upgrade processes, create deterministic test oracles, and ensure evidence-based promotion of changes in a remote US-based environment.

Qualifications

• Bachelor's degree in CS or related field.
• 15+ years of relevant experience in software engineering and QA.
• Experience designing developer- and test-infrastructure for large SaaS.
• Strong ability to influence across product, platform and operations.
• Experience with AI systems, coding models or agents.

Responsibilities

• Own the architecture for a change-safety loop across dev, CI, pre-prod, and customer environments.
• Drive change-impact analysis and dynamic assurance planning with data-driven evidence.
• Build AI-generated tests, fixtures, mocks and deterministic test oracles.
• Treat test infrastructure as a production-like engineering system and improve it.
• Lead release orchestration, upgrade processes and post-deployment verification.

Skills

Change-safety architecture

AI systems understanding

CI/CD and test architecture

Cross-functional influence

Deterministic verification

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

CI/CD tooling

Job description

About The Company

Our client is an AI-first enterprise planning software company on a mission to be the most value-creating platform for enterprises. Its platform integrates siloed planning capabilities and captures significant value leakage, helping global industry leaders plan smarter and faster and optimize their supply chains.

Location: Remote (US-based)

About The Company

Our client is an AI-first enterprise planning software company on a mission to be the most value-creating platform for enterprises. Its platform integrates siloed planning capabilities and captures significant value leakage, helping global industry leaders plan smarter and faster and optimize their supply chains.

About The Role

We are looking for an exceptional senior engineer to define and build the change-safety architecture for the company. The fundamental question for this role is: what are we about to change, what could it break, and what evidence is required to promote, hold or recover?

You will turn quality and release assurance into a continuously learning software-engineering system. The scope spans code, configuration, schema, models, infrastructure, deployment, customer-specific state, upgrades and post-release verification. This is a hands-on builder-architect role. You will set technical direction, write and review critical code, build the assurance primitives, and lead through technical influence across Reliability & Operations, Platform, Applications, AI, SecOps and Services/FDE.

Core technical thesis:

Every significant change should receive an assurance plan proportional to its actual risk and customer exposure. AI can understand changes and generate tests; deterministic oracles, exact state, policy and recovery determine whether evidence is sufficient to release.

What You'll Do

• Own the architecture for a change-safety loop across development, Continuous Integration (CI), shared pre-production, company-hosted environments and customer-managed environments, grounded in a precise model of code, configuration, schema, models, infrastructure, dependencies, deployments and feature controls.
• Drive change-impact analysis and dynamic assurance planning: use diffs, dependency structure, historical defects, production usage, current coverage and customer exposure to decide what evidence a specific change actually requires.
• Build AI-generated and AI-maintained executable tests, fixtures, mocks, synthetic data and fault injection, paired with deterministic test oracles and validators. Generated artifacts must be readable, reviewable, versioned and governed like production code.
• Treat test infrastructure and suite quality as an engineering system: flake, weak oracles, duplicate coverage, stale tests and excessive runtime are defects to be measured and repaired.
• Deliver customer-specific lifecycle assurance that binds evidence to the exact tested state and workload, distinguishes platform regression from customer incompatibility, and can run analyzers locally when customer data cannot move.
• Lead release and upgrade orchestration, residual-risk statements, post-deployment verification and explicit recovery; escaped defects feed back into impact models, tests and release policy.

First 90 Days

• Learn the software-delivery and customer lifecycle deeply: code and configuration paths, test infrastructure, shared pre-production, release and upgrade mechanics, customer-specific extensions, escaped-defect classes and current AI-led QA and upgrade automation assets.
• Establish a common taxonomy and baseline for changes, escaped defects, suite signal, flake, runtime, release failure, upgrade success, recovery readiness and customer impact.
• Define the initial change model, exact-state assurance contract, data-boundary patterns, evaluation framework, release policy and audit requirements.
• Select one or two narrow production pilots (for example a high-value change class, configuration path or upgrade flow) and produce an evidence-backed architecture direction and two-quarter delivery plan.

Over 12 to 24 Months

• Every significant change receives a dynamic assurance plan based on what changed, which customers and paths are exposed, historical failure evidence and the quality of existing coverage.
• Customer-specific releases and upgrades are verified against representative state with explicit residual risk and recovery.
• QA assets evolve continuously from code changes, production evidence and escaped defects rather than aging as a static test inventory.
• Risk-based selection, living-suite maintenance, performance and resilience coverage, upgrade automation and post-release verification are integrated into one release decision system.
• Low-risk, well-understood change classes progress toward policy-driven promotion, while the system abstains or escalates when evidence is insufficient.

Education

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Industrial Engineering, Engineering Management, or a related field. Master's degree preferred.

Experience

• 15+ years of relevant experience.
• Evidence that you have personally designed, built and operated developer-infrastructure, test-infrastructure, build/release, progressive-delivery or large-scale SaaS quality systems.
• Deep software and distributed-systems judgment. You can prototype, code, benchmark and debug the critical path yourself, not only define process or manage a QA organization.
• Strong understanding of build systems, CI/CD, test architecture, dependency and impact analysis, test selection, deterministic oracles, flake, release engineering, progressive delivery, rollback and production verification.
• Practical experience with modern AI systems, especially coding models and agents that can read repositories, generate executable tests, use tools and evaluate evidence. You understand their failure modes and how to constrain them with deterministic verification.
• A software-engineering view of quality: test code, test infrastructure, environments, release controls and recovery mechanisms are production systems with their own architecture and reliability requirements.
• Judgment to adapt practices from large-scale developer infrastructure to a configurable enterprise environment: shared pre-production, customer‑specific state, upgrades, multiple hosting models and strict data boundaries.
• The ability to influence across product, platform, QA, release, Services and operations teams without relying on formal authority, while respecting existing expertise and customer commitments.

About The Culture

Transparency and open communication are core to the culture, and collaboration thrives across all levels. The company is among the fastest-growing technology companies in its space, with a global presence across North America, Europe and Asia, and is an equal-opportunity employer that welcomes applicants from all backgrounds.