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Greenway Health Career Center in Bengaluru seeks an AI Director of Development Engineering to shape engineering strategy, drive modern software delivery, and lead high-performing teams. You will advance SDLC maturity, cloud delivery, and architecture governance while leveraging AI to improve delivery and decision-making.
The role emphasizes strategic leadership, cross-functional collaboration, and accountability for engineering outcomes in a fast-paced environment.
You will lead development of current and future capabilities while shaping engineering strategy, delivery standards, architecture direction, and team performance. You will act as a change agent for modern software delivery—using AI, automation, DevSecOps, CI/CD, cloud practices, quality gates, and engineering intelligence to improve how teams build and ship.
You bring strategic judgment and practical execution. We trust you to shape the future—and make it real.
Bachelor’s degree in Computer Science or a related field required. Master’s degree preferred.
Ten or more years of software development experience, including complex whole lifecycle software development management. Five or more years leading staff. Five or more years in software product development or management. Experience leading technology direction preferred.
Engineering strategy, SDLC transformation, agile leadership, cloud application development, CI/CD, architecture governance, quality practices, DevSecOps, technical debt management, roadmap trade-offs, stakeholder influence, change leadership, and team development.
Set vision, translate strategy into execution, make complex trade-offs, lead through change, influence executives and teams, develop leaders, evaluate technology direction, and govern responsible AI-enabled engineering practices.
Jira, VersionOne, Azure DevOps, TFS, MS Office, CI/CD platforms, cloud platforms, infrastructure as code tools, quality analytics, test automation frameworks, observability platforms, documentation systems, engineering intelligence tools, and approved AI-enabled engineering and leadership tools.
Use approved AI tools to support strategy development, architecture analysis, technical debt review, delivery-risk analysis, quality insights, documentation, stakeholder communication, and portfolio trade-off analysis. Validate AI-generated outputs before use. Do not enter sensitive, restricted, customer, healthcare, source code, financial, regulatory, or production data into unapproved tools. Human ownership remains required for strategy, architecture direction, people leadership, budget influence, risk acceptance, stakeholder alignment, and delivery outcomes.
Engineering strategy execution, SDLC maturity, product delivery quality, cloud and CI/CD adoption, technical debt reduction, team performance, roadmap trade-off quality, stakeholder trust, responsible AI adoption, and measurable improvement in product and engineering outcomes.
Establishes operational objectives, policies, procedures, and work plans and delegates assignments. Develops, modifies, and executes policies that affect immediate operations and may have company-wide effect. Accountable for department budget and business impact.