[Hiring] Delivery Engineer @FormAssembly Inc.

Role Description

We are seeking a Delivery Engineer to own and evolve the end-to-end engineering feedback loop—connecting development, testing, deployment, and production signals into a continuously improving system. This role goes beyond traditional QA or DevOps. You will design and operate the systems that determine how safely, quickly, and reliably we deliver software, while ensuring that every production signal feeds back into better engineering decisions. The ideal candidate is a systems thinker who understands that quality is not a phase—it is an emergent property of a well-designed delivery system.

Responsibilities

• Engineering Feedback Loop Ownership
  • Design, own, and evolve the end-to-end software delivery system
  • Ensure production signals (failures, latency, usage patterns) are continuously fed back into development and testing practices
  • Establish systems that improve both speed (velocity) and safety (reliability)
• Delivery and Release Strategy
  • Design and implement progressive delivery strategies:
  • Feature flags
  • Canary releases
  • Rolling/segmented deployments
  • Define and enforce risk-based release practices
  • Continuously reduce change failure rate while increasing deployment frequency
• CI/CD and Automation
  • Own and evolve CI/CD pipelines (GitHub Actions, AWS)
  • Build intelligent automation that prioritizes signal quality over volume
  • Optimize pipelines for speed, reliability, and developer experience
• Quality Engineering
  • Build and maintain automated testing systems (Playwright, API, integration)
  • Shift quality left (pre-merge validation, static analysis) and right (production validation)
  • Ensure tests reflect real-world failure modes, not just happy paths
• Observability and Production Intelligence
  • Implement and evolve observability systems (New Relic or equivalent)
  • Identify failure patterns, regressions, and performance anomalies
  • Turn production data into actionable engineering insights, not just dashboards
  • Reduce Mean Time to Recovery (MTTR) through improved detection and response systems
• Metrics and Continuous Improvement
  • Define, track, and improve key delivery metrics:
  • Deployment Frequency
  • Lead Time for Changes
  • Change Failure Rate
  • Mean Time to Recovery (MTTR)
  • Use metrics to drive system-level improvements, not vanity reporting
• AI-Assisted Engineering (Core Responsibility)
  • Lead adoption of AI-assisted engineering practices across:
  • Test generation
  • CI/CD optimization
  • Failure triage and debugging
  • Improve the signal-to-noise ratio of engineering feedback loops using AI
  • Partner with engineering teams to integrate AI into daily workflows
• Cross Team Influence
  • Define and standardize quality, reliability, and delivery practices across teams
  • Partner with QA, SRE, and product engineering to elevate system-wide outcomes
  • Act as a force multiplier, improving how all engineers ship software

Qualifications

• Strong understanding of software delivery systems and failure modes
• Hands-on experience with:
• CI/CD systems (GitHub Actions or equivalent)
• Automated testing frameworks (Playwright)
• Cloud environments (AWS preferred)
• Experience improving reliability in production systems
• Familiarity with observability platforms (New Relic)
• Proficiency in one or more languages (JavaScript/TypeScript, PHP/Laravel, Python)
• Solid understanding of shift left engineering and agile techniques

Preferred Qualifications

• Experience with progressive delivery techniques (feature flags, canary releases)
• Experience operating in high-scale SaaS environments
• Solid understanding of AI-assisted development tools (e.g., Claude, Copilot, Cursor)
• Experience designing systems that optimize DORA metrics
• Experience working with large-scale enterprise clients and delivering secure, high-availability solutions.

What Success Looks Like

• Engineers ship faster with fewer failures
• Production issues are detected earlier and resolved faster
• CI/CD pipelines provide high-confidence signals
• Every incident results in measurable system improvement
• AI meaningfully improves engineering productivity and quality
• The organization develops a culture of continuous improvement driven by feedback loops

Team Collaboration

This role works across engineering, partnering with:

• Software Engineering teams
• QA Engineering
• Systems Engineering (DevOps and Infrastructure)
• Engineering Leadership
• Customer Services
• Product Management

Benefits

• Health benefits (health, dental, vision) for Team Members based in the United States
• Mental Health benefits with SpringHealth
• 401(k) with 4% company match
• Unlimited PTO (with a required minimum use of 2 weeks per year) for Salaried/Exempt staff, or 4 weeks of paid vacation for hourly/non-exempt employees.
• 9 paid company holidays
• Flexible work schedule; work from anywhere!
• Generous Paid parental leave (up to 16 weeks)
• Charitable contribution match
• Budget for professional development
• Company provided Mac laptop