Engineering Lead Analyst – SonarQube & Code Quality Engineering - VP

The Engineering Lead Analyst – Sonar Qube & Code Quality Engineering is a senior-level engineering role responsible for leading static code analysis, automated code quality governance, security vulnerability remediation, and AI-augmented developer enablement across enterprise software delivery pipelines.

In this role, you will champion software reliability, maintainability, clean-coding standards, and automated quality gates. You will partner with development teams, system architects, and platform engineering to integrate and manage enterprise-scale code quality platforms (such as Sonar Qube) both on-premises and in cloud/SaaS environments. Additionally, you will drive modern engineering practices by embedding Behavior-Driven Development (BDD) within your own software delivery and leveraging Agentic AI workers and Model Context Protocol (MCP) architectures to optimize developer experience, streamline code governance, and boost engineering velocity.

• Lead the architecture, deployment, administration, and continuous enhancement of enterprise Static Application Security Testing (SAST) and Code Quality platforms (e.g.,
  Sonar Qube
  , Deep Source, Codacy, Semgrep).
• Configure, calibrate, and enforce automated Quality Gates, code rulesets, technical debt calculation models, and code-coverage baselines across multi-language enterprise repositories.
• Oversee version upgrades, patching, high availability, and operational maintenance for on-premises and SaaS/cloud-hosted code quality infrastructure.

• Embed automated code quality scanning and gating into modern CI/CD orchestration platforms (e.g.,
  Tekton
  , Harness
  , Jenkins
  , Git Lab CI, Git Hub Actions).
• Standardize build-time and pull-request scanning workflows, ensuring seamless developer feedback loops, fast pipeline execution, and automated branch policy validation.
• Containerize and maintain scanning tools and quality agents using Docker, Podman, and Open Shift/Kubernetes environments.

• Leverage existing automated Behavior-Driven Development (BDD) testing frameworks (e.g., Cucumber, Behave) within own day-to-day software development lifecycle to ensure all platform features, integrations, and automation scripts promoted to production are of the highest quality.
• Build reliability, robustness, and fault tolerance into all delivered engineering components, maintaining high test coverage and rigorous functional/regression verification prior to release.
• Ensure automated test suites run seamlessly as mandatory validation gates within CI/CD pipelines before promotion to production environments.

• Architect, configure, and operationalize Agentic AI workers and Model Context Protocol (MCP) tool ecosystems to enhance developer productivity and modernize code review workflows.
• Integrate AI-driven agents into development environments and CI/CD pipelines to assist engineers with automated quality triage, intelligent remediation suggestions, boilerplate generation, and static analysis interpretation.
• Continuously evaluate and implement emerging AI tools and MCP servers that improve Developer Experience (Dev Ex), reduce manual toil, and accelerate engineering velocity across the firm.

• Partner with Cyber Security, Architecture, and Application teams to triage, track, and remediate static code vulnerabilities, Common Vulnerabilities and Exposures (CVEs), and OWASP Top 10 risks.
• Conduct deep-dive root cause analyses (RCA) on recurring defect patterns, code smells, architectural bottlenecks, and pipeline…