Own DevOps and QA outcomes across assigned programs, ensuring delivery milestones are met in line with agreed timelines.
Partner closely with various teams to ensure smooth, predictable execution.
Provide clear technical direction and decision‑making, reducing ambiguity for internal teams and external partners.
Provide hands‑on technical leadership across:
o DevOps and CI/CD pipelines
o QA automation frameworks
o Cloud platforms and tooling
o Engineering standards and best practices
Define, standardize, and enforce processes, tools, and architectural patterns to ensure consistency and reuse across teams.
Lead modernization of CI/CD pipelines, test automation frameworks, and selected platform components, creating long-term leverage across multiple programs.
Oversee QA strategies and testing practices across teams.
Establish quality metrics and acceptance criteria.
Drive test automation initiatives and coverage improvements.
Monitor defect trends and quality indicators.
Leverage AI‑driven and automation‑first approaches to improve:
o Delivery speed and quality
o Test coverage and reliability
o Pipeline efficiency and release confidence
o Observability and operational insight
Embed AI capabilities pragmatically (e.g. test generation, pipeline intelligence, release insights, automated validation) with a focus on high-value adoption.
Act as a translation layer between strategy and execution, converting enterprise standards into practical, team‑level implementation.
Serve as a technical authority for assessing solutions, tooling options, and architectural tradeoffs.
Drive strong day‑to‑day collaboration with engineering teams, accelerating adoption of standard platforms and tooling.
Requirements
8+ yrs experience leading DevOps, QA and platform engineering initiatives in complex, multi-team delivery environments.
Strong understanding of software architecture patterns and principles.
Deep knowledge of SDLC methodologies and development best practices.
Deep expertise in CI/CD pipelines, cloud platforms, infrastructure tooling, and QA automation.
Knowledge of security, performance, and scalability patterns.
Experience with quality assurance frameworks and methodologies.
Proven ability to design and evolve scalable, secure, and maintainable delivery platforms.
Experience embedding automation and AI‑assisted capabilities into engineering workflows.
Proven ability to provide clear technical leadership across teams.
Strong stakeholder management skills, with the ability to align product, engineering, security, and enterprise architecture.
Bachelor's degree in computer science or related field.