Renesas Electronics

Technology

DirectorofSoftwareEngineering

₹45–75L ~AI est. Hyderabad, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for director candidates.

The Brief

“Director of Software Engineering at Renesas Electronics. Skills: Software Engineering Leadership, Cloud Architecture, DevOps, AI/ML Integration. Lead and manage software engineering teams. Oversee the design, development, and deployment of software”

What You'll Achieve.

Deliver high-quality software on time; Improve system performance and reliability; Enhance team productivity and efficiency; Drive technical innovation; Ensure successful product launches

Industry & Context.

Technology
Problems you'll solve

Root cause analysis; System troubleshooting; Performance optimization; Complex problem solving

What They're Looking For.

Must Have

5+ years of experience in software engineering, 3+ years of experience in a leadership role, Bachelor's degree in Computer Science or related field, Experience with cloud platforms (AWS, Azure, GCP), Experience with CI/CD pipelines, Experience with containerization technologies (Docker, Kubernetes)

Nice to Have

Master's degree in Computer Science or related field, Experience with AI/ML technologies, Experience with data engineering tools and platforms, Experience with cybersecurity best practices

What You'll Do.

Lead and manage software engineering teams

and deployment of software

Define and implement engineering best practices

Drive technical strategy and roadmap

and security of systems

Mentor and develop engineering talent

Collaborate with product management and other stakeholders

Manage project timelines and resources

Foster a culture of innovation and continuous improvement

Oversee cloud infrastructure and DevOps practices

Guide the integration of AI/ML technologies

Ensure adherence to cybersecurity best practices

How You'll Work.

Team & Collaboration

Cross-functional teams; Product management; Stakeholder alignment; Engineering leadership

Communication Scope

Technical presentations; Cross-functional communication; Executive reporting

Process & Methodology

Agile methodologies, Scrum, Roadmap planning, Resource allocation, Risk management

Full Job Description

Renesas is one of the top global semiconductor companies in the world. We strive to develop a safer, healthier, greener, and smarter world, and our goal is to make every endpoint intelligent by offering product solutions in the automotive, industrial, infrastructure and IoT markets. Our robust product portfolio includes world-leading MCUs, SoCs, analog and power products, plus Winning Combination solutions that curate these complementary products. We are a key supplier to the world’s leading manufacturers of electronics you rely on every day; you may not see our products, but they are all around you. Renesas employs roughly 21,000 people in more than 30 countries worldwide. As a global team, our employees actively embody the Renesas Culture, our guiding principles based on five key elements: Transparent, Agile, Global, Innovative, and Entrepreneurial. Renesas believes in, and has a commitment to, diversity and inclusion, with initiatives and a leadership team dedicated to its resources and values. At Renesas, we want to build a sustainable future where technology helps make our lives easier. Join us and build your future by being part of what’s next in electronics and the world. In this role, you will lead the definition and execution of AI/ML-driven initiatives, drive adoption of ML/AI across frontend and backend design and development flows across the company, enable next-generation intelligent design automation capabilities, and collaborate with cross-functional leaders to integrate AI into engineering productivity, automation, and decision-making processes. Job Responsibilities * Define and own the AI/ML strategy for Engineering group’s software and design flows * Lead the transformation of semiconductor design workflows by deploying AI-driven (agentic) solutions across Frontend (modelling, synthesis, optimization) and Backend (place-and-route, timing closure, physical optimization) * Drive end-to-end integration of AI into engineering toolchains * Establish sca

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