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https://bayt.page.link/GozFyeB58YaadD227
العودة إلى نتائج البحث‎

VP Engineering & Managing Director, India

اليوم 2026/09/06
خدمات الدعم التجاري الأخرى
أنشئ تنبيهًا وظيفيًا لوظائف مشابهة
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الوصف الوظيفي

About Platform Services


The energy transition has moved past the technology-proving phase. Today, the defining challenge is orchestrating millions of distributed energy assets — reliably, securely, and at the pace the grid demands.


Platform Services is the digital growth engine for DNV Energy Systems North America, built on a fundamental conviction: the grid doesn't need more hardware. It needs better intelligence.


Our mission is to bridge infrastructure complexity with commercial execution by delivering secure, AI-native SaaS platforms that turn digital ambition into operational reality for Tier-1 utilities and energy operators.


Our vision is to unify the fragmented legacy architectures of utility program operations into a single, modern data model — building the operational nervous system that accelerates the path to decarbonization. As we scale to support 4x customer-account growth over the next three years, this is one of the most consequential platform-engineering challenges in the energy sector.


The VP Engineering & Managing Director India Operations is the senior India-based executive at Platform Services, accountable for the technology foundation of the business and for the day-to-day health and culture of the Chennai site. This is a dual-mandate role: chief technical leader for the SaaS platform, cloud and AI infrastructure, data and platform engineering, and engineering productivity and senior site executive for the 200+ person Chennai organization, supported by Director of India Operations.
The role exists at the intersection of platform engineering, data, and AI-native development. The leader translates product strategy into secure, reliable, production-grade systems while building an engineering organization that uses AI deliberately and responsibly. They drive the platform and infrastructure investments required to scale to 4x customer-account growth — multi-program platform adoption, expanded transaction volumes, and the technical foundation for the AI tier.
Key Responsibilities
Platform & Engineering Leadership
  • Own the SaaS platform architecture — cloud infrastructure, DevSecOps, data engineering, AI model serving, MLOps pipelines.
  • Architect and deliver the unification of legacy data models into a single, modern platform foundation to unlock enterprise-scale cross-selling of multi-program platform thesis and AI capability scaling.
  • Translate product strategy into scalable, maintainable, production-ready systems with clear engineering ownership and delivery discipline.
  • Own engineering-side quality assurance, platform reliability, deployment velocity, and engineering productivity.
  • Drive disciplined execution using DORA metrics, automation, and continuous improvement practices.
AI-Native Engineering Practices
  • Drive deliberate adoption of AI-native engineering practices — responsible use of LLMs for coding, testing, documentation, code review, and operational tooling.
  • Define how engineering teams leverage AI to materially improve development velocity while preserving engineering fundamentals (code quality, testability, security posture, observability).
  • Ensure AI-enabled and data-driven capabilities are production-grade, secure, scalable, and operable — not POCs in production.
Architecture, Platforms & Interoperability
  • Oversee system architecture, platform design, and integration patterns supporting long-term scalability and maintainability.
  • Promote reusable components, shared services, APIs, and consistent data and integration standards across the platform.
  • Guide the appropriate balance between low-code platforms (eTRACK+ workflow heritage) and custom engineering — knowing when each is the right tool.
  • Enable interoperability across core systems in partnership with Product and adjacent digital teams.
DevOps, Reliability & Security
  • Establish and oversee end-to-end DevOps practices — CI/CD, automated testing, deployment, monitoring, incident management.
  • Ensure enterprise-grade reliability, performance, and availability of all production systems.
  • Act as the matrixed Operator — execute security remediations defined by Information Security, run production infrastructure that serves AI models defined by Enterprise AI.
  • Lead engineering readiness and compliance for SOC 2 Type II, ISO 27001, and secure development standards.
India Site Leadership
  • Serve as the senior Chennai site executive — accountable for culture, engagement, talent retention, and the site's external presence.
  • Own India HR partnership and statutory compliance — PF, ESIC, DPDP Act, POSH, gratuity, and related obligations — supported by the Director of India Operations.
  • Oversee facilities, site operations, and India business continuity.
  • Build and sustain a high-performance, accountable engineering culture that India talent chooses to join and stay at.
Cross-Functional Partnership
  • With Product: Engineering capacity allocation, delivery trade-offs, technical roadmap input. Success looks like: clear quarterly capacity commitments, transparent trade-off conversations, no roadmap surprises in QBRs.
  • With Enterprise AI: AI infrastructure boundary, MLOps ownership, model serving reliability. Success looks like: jointly-owned model serving uptime, no friction at the capability/infrastructure boundary.
  • With Trust & InfoSec: Independent policy execution. Success looks like: high security remediation rate, no release-blocking conflicts.
  • With US-based leadership: Senior India-based technical voice in global forums. Success looks like: visible presence at customer architecture reviews, executive QBRs, and strategic planning.
Success Metrics
  • Unified data model Phase delivered; multi-program platform foundation operational.
  • Platform uptime ≥99.95% on enterprise tier with weekly production releases and no quality regressions.
  • AI model serving uptime ≥99.9% and reliable MLOps pipelines (jointly owned with Enterprise AI team).
  • Security remediation rate >95% against Trust & InfoSec-defined SLAs.
  • Measurable engineering productivity improvement via AI-native practices.
People Development
  • Build and strengthen a culture based on our Purpose, Vision, and Values (PVV).
  • Build a culture of learning and, through empowerment, ensure staff are supported.
  • Focus on driving the growth of the business through implementation of people management strategies and a well-aligned workforce plan.
  • Drive recruitment and staff retention across the department.
  • Collaboratively develop competency and succession planning for critical roles and capabilities within the department.
  • Identify and plan staff development using the DNV development model (70:20:10) to ensure continuous improvement and service delivery.
  • Ensure the team is utilized at the appropriate level given the mix of business development, innovation, and delivery responsibilities.

About Energy Systems
We help customers navigate the complex transition to a decarbonized and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments to navigate the many complex, interrelated transitions taking place globally and regionally, in the energy industry.
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