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Design Methodology in India

967 active opportunities · Updated October 2026

Explore current design methodology jobs across India. Filter by work mode, employment type, experience, department, date posted and distance.

T
📍 Bengaluru, KARNATAKA, India
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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly skilled and motivated Senior Design Verification Engineer to join our team. In this role, you will be responsible for the end-to-end verification of our IOMMU (Input/Output Memory Management Unit) IP. You will play a critical role in ensuring the functional correctness and performance of the design, taking ownership of the verification process right from the initial specification understanding down to final coverage closure. This role is hybrid, based out of Bangalore, India. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You have hands-on experience in ASIC or SoC verification using SystemVerilog and UVM. You enjoy debugging complex design and verification issues and working closely with cross-functional teams. You’re comfortable building verification environments from scratch and driving coverage closure. You have familiarity with standard bus protocols and modern verification tools. What We Need Experience owning block or subsystem-level verification from test planning to sign-off. Strong understanding of constrained-random verification, coverage analysis, and regression debugging. Familiarity with proto

NR
📍 Bengaluru, India
✓ High-confidence listingCompany trend -12.5%
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We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity AI is a top strategic priority for New Relic, and the Bengaluru design team is at the center of it. The team works across three closely related product clusters: autonomous incident response (SRE Agent, Autopilot, and Intelligent RCA), the intelligence and platform layer that powers them (Ground Truth, Agentic Platform, and New Relic AI), and AIOps for event correlation and incident management. These products share a common design challenge: users need to trust systems that act autonomously, and building that trust through good design is genuinely hard work. This is an on-site role in Bengaluru. Your designers are there, and many of your engineering and product partners are too. Being present — in standups, reviews, and the quick conversations before a decision gets made — is part of how you'll build the relationships that make design effective. You'll also collaborate with design, product, and engineering partners in the US and Spain, so operating across time zones and communicating well in writing are part of the job. You'll manage a small team of designers and own the quality of the work across these products. The design questions here don't have established answers — how do you make an autonomous system legible? How do you build user trust in AI-generated root cause analysis? How do you design a handoff from machine decision to human judgment? If you're already working in AI product design, or actively building toward it, and you want to lead a team

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