The Senior Solutions Architect will work with leading Enterprise ISVs to design, build, optimize, and deploy production-grade Agentic AI systems on NVIDIA’s accelerated computing platform. This role involves partnering with strategic software companies to translate advanced AI capabilities into reliable enterprise products. The architect will lead technical projects from exploration through to production rollout and field enablement. The focus is on adopting NVIDIA technologies to bring next-generation AI products to market.

• BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.
• 8+ years of engineering, solutions architecture, applied ML, or technical deployment experience.
• Consistent track record leading complex AI, ML, distributed systems, or enterprise software deployments from prototype to production.
• Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.
• Strong programming and debugging skills in Python and Linux environments, with experience in PyTorch, TensorFlow, or similar deep learning frameworks.
• Deep understanding of agentic AI architectures, including tool use, orchestration, memory, retrieval, planning, evaluation, guardrails, and failure handling.
• Experience with model customization or post-training techniques such as SFT, RL/RLHF/RLAIF, DPO or relevant equivalent experience.

• Lead technical delivery for strategic Agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale.
• Design and build enterprise-grade agentic systems, including multi-agent workflows, tool-using agents, RAG-integrated applications, planning, memory, evaluation, and guardrail patterns.
• Lead deep architecture reviews with partner engineering teams, driving tradeoffs across model quality, latency, efficiency, cost, retrieval quality, reliability, safety, security, and observability.
• Build hands-on PoCs, benchmarks, reference architectures, and reusable blueprints that help Enterprise ISVs and NVIDIA field teams move from exploration to production.
• Guide partners on model customization and post-training workflows, including supervised fine-tuning, reinforcement learning methods, human or AI feedback, direct preference optimization, PEFT/LoRA, synthetic data generation, evaluation, and regression analysis.
• Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering to improve platforms, tools, and field guidance.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.