Engineering Lead Analyst – SonarQube & Code Quality Engineering - VP

The Engineering Lead Analyst – SonarQube & 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 SonarQube) 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. Key Responsibilities 1. Code Quality & Static Analysis Platform Ownership

• Lead the architecture, deployment, administration, and continuous enhancement of enterprise Static Application Security Testing (SAST) and Code Quality platforms (e.g., SonarQube , DeepSource, 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. 2. CI/CD & Pipeline Integration
• Embed automated code quality scanning and gating into modern CI/CD orchestration platforms (e.g., Tekton , Harness , Jenkins , GitLab CI, GitHub 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 OpenShift/Kubernetes environments. 3. Automated BDD Testing & Robust Engineering Delivery
• 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. 4. Agentic AI & Model Context Protocol (MCP) Enablement
• 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 (DevEx), reduce manual toil, and accelerate engineering velocity across the firm. 5. Technical Governance, Security Remediation & Root Cause Analysis
• 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 failures.
• Provide subject matter expertise (SME) on clean coding standards, refactoring strategies, and design patterns across languages including Java, Python, JavaScript/TypeScript, and Go. 6. Leadership, Mentorship & Stakeholder Management
• Serve as the technical authority on code quality, static analysis, and AI-enabled engineering practices for internal stakeholders and engineering leadership.
• Advise, mentor, and upskill junior engineers and development teams on best practices for clean code, unit testing, BDD execution, and leveraging AI developer tools safely.
• Collaborate with Product Managers, Solution Architects, and Release Engineering to define quality roadmaps, KPIs, and engineering velocity metrics. 7. Risk, Compliance & Governance
• Appropriately assess risk during technical decision-making, demonstrating strict consideration for the firm’s reputation and safeguarding Citi’s assets.
• Ensure all quality tools, pipelines, AI agents, and processes adhere to Citi compliance policies, internal audit standards, information security guidelines, and regulatory requirements. Qualifications & Competencies Experience & Technical Background
• 13+ years of relevant experience in a Software Engineering, DevOps, or Code Quality Engineering role within a large-scale, complex, or global enterprise (Financial Services experience strongly preferred).
• Static Analysis Platforms: Proven hands-on administration and engineering experience with SonarQube (Enterprise/Data Center edition preferred) and related static analysis/linter tooling (Semgrep, Codacy, DeepSource, Checkmarx, SonarLint).
• Programming Proficiency: Strong development or scripting skills in one or more core languages: Java , Python , JavaScript/TypeScript , or Go .
• CI/CD & DevOps: Deep working knowledge of CI/CD pipeline automation tools such as Jenkins , Harness , Tekton , or GitHub Actions .
• Containers & Cloud: Practical experience with container technologies ( Docker , Podman , OpenShift , or Kubernetes ).
• BDD & Automated Testing: Proven experience leveraging existing BDD frameworks (Cucumber, Behave) and unit/functional test suites (JUnit, PyTest, Playwright, Cypress) within personal software development workflows to deliver production-grade, highly reliable code.
• Agentic AI & Tooling: Familiarity or hands-on experience with Agentic AI architectures , Model Context Protocol (MCP) server integration, LLM-based coding assistants, or AI-augmented developer tooling.
• Cybersecurity & Compliance: Demonstrated experience in vulnerability management, static security scanning, and automated gating for security compliance. Soft Skills & Leadership Capabilities
• Exceptional written and verbal communication skills with the ability to convey complex technical concepts to non-technical stakeholders.
• Strong analytical and diagnostic problem-solving skills with a proactive approach to continuous improvement.
• Proven track record of driving operational process improvements and reducing technical debt.
• Ability to thrive in a global matrixed organization, managing tight deadlines and competing priorities independently. Education
• Bachelor’s Degree / University Degree in Computer Science, Computer Engineering, Information Technology, or equivalent practical experience.
• Master’s Degree in a related technical discipline is preferred. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Systems & Engineering ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: Tampa Florida United States ------------------------------------------------------ Primary Location Full Time Salary Range: $113,840.00 - $170,760.00 In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off pac