Principal Architect, DevSecOps & Platform Engineering

As a Principal Architect within the Chief Data Office (CDO), you will lead the technical vision and architecture strategy for enterprise-scale DevSecOps and platform engineering initiatives. You will define and implement secure, scalable, and automated software delivery frameworks that enable engineering teams to deliver high-quality applications reliably and efficiently., This role requires deep expertise in Python, cloud-native architectures, CI/CD automation, and security-first engineering practices. You will partner with senior leadership and cross-functional teams to drive innovation, establish standards, and transform release engineering across the organization. What You'll Do Architecture & Strategy

• Define and lead the architecture roadmap for cross-platform engineering and DevSecOps transformation
• Design and govern scalable systems, APIs, CI/CD frameworks, and enterprise platforms
• Establish architecture standards, review boards, and technical governance processes
• Create long-term technology strategies, roadmaps, and architectural decision frameworks

DevSecOps & Platform Engineering

• Architect enterprise-grade CI/CD pipelines using GitHub Actions and reusable workflows
• Build and standardize Infrastructure-as-Code (IaC) templates and deployment patterns
• Integrate and enforce security controls across the SDLC:

• Static Code Analysis (Sonar)
• SAST (Checkmarx)
• SCA (Black Duck)
• Secret Scanning (GitHub)
• DAST

• Design secure, automated release pipelines with policy enforcement and audit capabilities
• Establish golden-path repositories and CI/CD standards
• Drive adoption of DevSecOps, GitOps, and DORA metrics

Cloud & Deployment Architecture

• Define deployment strategies for OpenShift/Kubernetes platforms
• Architect release orchestration using Harness CD (or equivalent), including promotion, approvals, and rollback
• Enable reliable, scalable, and compliant application deployment pipelines

Leadership & Influence

• Serve as a trusted advisor to senior leadership on engineering strategy and innovation
• Mentor engineers and architects across the organization
• Drive adoption of modern engineering practices (SRE, DevSecOps, platform engineering)
• Lead evaluation and adoption of emerging technologies, The Chief Data Office (CDO) enables enterprise-scale data and analytics across a global financial organization, supporting over 70 million customers. The Cross Platform Engineering team builds the standards, tools, and automation that power secure, scalable, and efficient software delivery.

This role contributes to Path to Production - Release Cargo Management (P2P-RCM), an enterprise initiative designed to standardize release processes, automate compliance, and accelerate delivery across all application types. Why This Role Matters

• Drive enterprise-wide DevSecOps transformation
• Influence architecture at scale across critical platforms
• Improve reliability, security, and developer productivity
• Enable faster, safer delivery for mission-critical applications

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• 12+ years of experience in software engineering and architecture
• Extensive expertise in Python and building large-scale distributed systems
• 10+ years building web applications and APIs (Django, FastAPI, Flask)
• 10+ years designing CI/CD systems and DevOps platforms
• Experience with GitHub Actions, reusable workflows, and pipeline automation
• Strong experience with cloud-native platforms (Kubernetes/OpenShift)
• Proven expertise integrating security tools into CI/CD pipelines
• Experience designing deployment automation with Harness CD (or similar)
• Deep understanding of DevSecOps, system reliability, and secure architecture, * Experience contributing to open-source projects such as:

• Conda-Forge
• Pixi Package Manager

• Expertise building GitHub Actions and CI/CD automation frameworks
• Advanced knowledge of platform engineering, IaC, and GitOps practices
• Experience with data platforms, pipelines, and orchestration tools (Airflow, MLFlow, Kedro)
• Strong background in testing frameworks (Pytest) and engineering best practices
• Experience with enterprise-scale architecture governance
• Familiarity with AI-assisted development tools (e.g., GitHub Copilot)
• Proven success leading large-scale engineering transformations