Senior Developer Relations Manager - FSI

NVIDIA · Mumbai

Source and collection record

Last observed by our collector: 8 October 2026 at 10:51 pm IST. This is not a manual review or a confirmation from the employer.

Job type and experience labels are automated discovery categories. The employer determines eligibility. Retained employer experience wording: 8+ years.

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Retained employer experience wording: 8+ yearsAttendance and availability: I checked the employer page for work location, office attendance, start date and duration.Current requisition: I checked the current employer requisition and its application requirements.

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Collected role description

requirements for NVIDIA product and engineering teams. What We Need To See: Bachelor’s degree in engineering, computer science, data science, or a related technical field—or equivalent experience. 8+ years of experience in AI platforms, cloud infrastructure, fintech, payments, banking technology, data science, solution architecture, or developer ecosystems. Strong knowledge of machine learning, deep learning, generative AI, real-time inference, data engineering, MLOps, and cloud-native systems. Experience with regulated environments, high-availability systems, privacy, security, compliance, and production observability. Ability to profile AI workloads across compute, memory, I/O, networking, latency, throughput, batching, GPU suitability, and cost-performance tradeoffs. Ability to lead technical and business discussions with engineering, platform, risk, and senior stakeholder teams. Excellent communication, stakeholder management, execution, and cross-functional collaboration skills. Working knowledge of NVIDIA AI technologies, including NIM, Triton, Tensor RT, Tensor RT-LLM, CUDA, Nsight, RAPIDS, NGC, NVIDIA AI Enterprise, and GPU Operator. Ability to apply NVIDIA technologies to fraud, risk, document AI, customer service, real-time decisioning, feature engineering, and large-scale analytics workloads. Ability to design secure, observable, compliant, and cost-efficient GPU-accelerated deployments across cloud, data-center, Kubernetes, and hybrid environments. Ways To Stand Out from the crowd: Experience in payments, fintech, banking technology, financial infrastructure, fraud platforms, compliance technology, or risk systems. Experience creating workload qualification frameworks, benchmark plans, or technical decision guides that help financial services developers decide when GPU acceleration is the right fit. Knowledge of fraud models, risk models, graph analytics, transaction intelligence, document AI, or real-time decisioning systems. Prior experience turning NVIDIA GPU computing, AI software, model serving, or acceleration libraries into regulated workload playbooks or production adoption plans. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.

Collected experience requirement

8+ years