Senior Solutions Architect, Agentic AI

About the role

The role involves developing, building, and deploying agentic AI systems with top Media & Entertainment (M&E) companies. Partnering with customers from studios, streaming and broadcast platforms, gaming, advertising, content creation, and the media supply chain, you will transform frontier large language model (LLM) capabilities into autonomous agents at production scale.

Responsibilities

• Architect, build, and ship end-to-end Agentic AI applications for M&E use cases—spanning multi-agent coordination, long-horizon reasoning, planning, and tool use—along with high-performance RAG pipelines over heterogeneous media assets (text, code, images, audio, video) to tackle real production challenges such as content generation, localization, metadata enrichment, personalization, recommendation, and ad operations.
• Act as a hands-on technical advisor and main domain expert during the pre- and post-sale stages. Work closely with customer AI researchers, engineers, and developers to build, prototype, and deploy Agentic solutions on NVIDIA platforms.
• Optimize inference performance and total cost of ownership using the full NVIDIA AI inference stack—and build hands-on proofs-of-concept, reference architectures, and reusable blueprints that serve as production templates and accelerate time-to-value.
• Post-training open sourced models to meet the M&E requirements.
• Partner with NVIDIA engineering, product, and sales teams to secure build wins, translate customer feedback into actionable product and roadmap insights, and scale global expertise through technical collateral, workshops, and developer communities.

Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience)
• 8+ years as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments
• Validated experience building sophisticated agentic and multi-agent AI systems using orchestration frameworks such as LangGraph, LlamaIndex, CrewAI, LangChain, OpenAI Agents SDK —including tool-using and routing agents. Solid understanding of MCP and A2A is vital.
• Strong background in PyTorch and distributed GPU (post-)training. Able to quickly prototype and build scalable GPU-accelerated architectures. Applies test-time compute, reinforcement learning, inference optimization, and post-training. Deploys workloads at scale on public cloud (AWS, GCP, Azure, OCI) or on-premise.
• Strong grasp of the M&E industry paired with excellent communication and presentation skills. Able to explain sophisticated ideas to both technical and non-technical groups. Works well with executives, partners, and engineering teams. Leads projects from start to finish in a fast-paced, multitasking setting.

Qualifications

• Practical experience working directly with the NVIDIA agentic AI software stack—NVIDIA NIM, NeMo Framework, NeMo Retriever, NeMo Agent Toolkit, Dynamo, Triton Inference Server, TensorRT-LLM, and AI Blueprints.
• Expertise building LLM evaluation harnesses, benchmarking systems, observability platforms, and safety guardrails, plus fine-tuning and optimizing reasoning-focused LLMs and SLMs through timely engineering and quantization.
• Experience developing production-grade deployment patterns using Kubernetes/OpenShift, CI/CD automation, and secure cloud-native infrastructure, with familiarity in large-scale data processing and distributed/parallel computing frameworks (e.g., Spark, Dask).
• Proven experience handling NVIDIA GPU architectures, CUDA-X libraries (cuBLAS, cuDNN, RAPIDS), and HPC technologies (NCCL, InfiniBand, MPI, NVLink), along with familiarity in large-scale data processing and distributed/parallel computing frameworks (e.g., Spark, Dask).
• A strong public profile (blogs, GitHub, conference talks) that demonstrates your expertise and passion for agentic AI. Widely considered to be one of the technology world’s most desirable employers.

Skills

• Agentic AI development
• Multi-agent systems
• High-performance RAG pipelines
• Optimization of inference performance
• Deployment on NVIDIA platforms
• Communication and presentation skills
• Leadership in project management

Benefits

• NVIDIA offers highly competitive salaries and a comprehensive benefits package.
• You will be eligible for equity and benefits.

Pay

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

Schedule

Full time