Senior AI Solutions Engineer – Customer Success and Deployment

Senior AI Solutions Engineer – Customer Success and Deployment

Oracle Government, Defense & Intelligence seeks a highly technical and customer-focused AI Solutions Engineer to serve 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.

This role combines deep AI/ML engineering expertise with customer engagement, solution architecture, performance optimization, and operational excellence. The successful candidate will work directly with customer technical teams, business stakeholders, Oracle engineering, product management, operations, and cloud infrastructure teams to ensure deployed AI solutions meet mission requirements, performance expectations, and operational objectives.

The ideal candidate can translate business goals into technical solutions, explain complex AI concepts to both executive and technical audiences, and act as a trusted advisor throughout deployment, testing, optimization, and production operations.

• 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 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.
• Interpret testing and benchmark results, explain performance outcomes, and provide recommendations for continuous improvement.
• 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.
• Analyze telemetry, observability data, and service metrics to troubleshoot issues, support incident investigations, and identify optimization opportunities.
• Provide customer and field feedback to influence product direction, service improvements, and engineering roadmaps.

• Must possess or have the ability to obtain and maintain an active TS/SCI with FS poly.
• Full‑time in‑office position.

• 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.

• Experience with enterprise AI platforms such as Oracle GenAI Service, Azure OpenAI Service, Amazon Bedrock, Google Vertex AI, or similar technologies.
• Strong understanding of cloud infrastructure, networking, security, distributed systems, and cloud‑native architectures.
• Familiarity with Kubernetes,…