Senior AI Solutions Engineer – Customer Success and Deployment

About the role

The Senior AI Solutions Engineer – Customer Success and Deployment role at Oracle Government, Defense & Intelligence is dedicated to serving as the primary technical interface between Oracle and strategic customers deploying Large Language Models (LLMs) on Oracle Cloud Infrastructure (OCI), including OCI Isolated Regions and sovereign environments.

Responsibilities

• Serve as the primary technical representative for Oracle during customer AI and Generative AI deployments.
• Build trusted advisor relationships with customer engineering, operations, security, and leadership teams.
• Translate customer mission requirements, business objectives, and operational constraints into scalable AI deployment strategies.
• Communicate model capabilities, limitations, performance expectations, and technical tradeoffs to both technical and executive audiences.
• Support the deployment, validation, and optimization of Large Language Models (LLMs) running on Oracle GenAI Services and OCI infrastructure, including isolated and sovereign cloud environments.
• Analyze and improve solution performance across throughput, latency, Time to First Token (TTFT), scalability, context utilization, resource efficiency, and overall user experience.
• Guide customers through benchmarking, acceptance testing, production readiness, and operational optimization activities.
• Recommend best practices for model selection, prompting strategies, Retrieval-Augmented Generation (RAG) architectures, and AI solution design.
• Understand customer evaluation methodologies, benchmark frameworks, and acceptance criteria.
• Evaluate model behavior across domain-specific and mission-critical use cases to ensure solutions align with customer objectives.
• Partner with Oracle engineering, product management, cloud operations, networking, security, and support teams to deliver successful customer outcomes.
• Drive resolution of complex deployment, performance, infrastructure, and operational challenges across multiple organizations and environments.
• Provide customer and field feedback to influence product direction, service improvements, and engineering roadmaps.

Qualifications

• MUST possess or have the ability to obtain and maintain an active TS/SCI with FS poly.
• Strong understanding of Large Language Models (LLMs), Generative AI systems, inference architectures, and production AI application deployment.
• Experience with prompt engineering, Retrieval-Augmented Generation (RAG), embedding models, vector databases, model evaluation methodologies, and model adaptation techniques.
• Ability to explain AI model capabilities, limitations, risks, and expected behaviors to technical and non-technical stakeholders.
• Strong understanding of cloud infrastructure, networking, security, distributed systems, and cloud-native architectures.
• Familiarity with Kubernetes, containerized applications, and supporting production workloads in regulated, sovereign, government, or isolated cloud environments.
• Experience integrating LLM services and APIs into enterprise applications and business workflows.
• Experience presenting technical solutions to customer executives, architects, and engineering teams.
• Experience with OCI and Oracle Cloud technologies.
• Experience supporting AI workloads in OCI Dedicated Region, OCI Isolated Region, government cloud, or sovereign cloud environments.
• Knowledge of GPU infrastructure and AI inference platforms.
• Familiarity with NVIDIA AI ecosystem technologies.
• Experience conducting customer-facing architecture reviews and technical workshops.
• Understanding of AI governance, security, compliance, and responsible AI principles.
• Experience with benchmark analysis and model evaluation frameworks.
• Background in Site Reliability Engineering (SRE), DevOps, Cloud Engineering, or AI Platform Engineering.