Senior AI Solutions Engineer - Customer Success and Deployment

Oracle Government, Defense & Intelligence  is seeking 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.

• MUST possess or have the ability to obtain and maintain an active TS/SCI with FS poly

• Full time in office position.

Key Responsibilities

Customer Technical Leadership

• 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.

AI Solution Deployment & Optimization

• 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.

Customer Validation & Advisory

• 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.

Cross-Functional Execution & Operatins

• 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.

Required Qualifications

• MUST possess or have the ability to obtain and maintain an active TS/SCI with FS poly

AI/ML Expertise

• 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.

Cloud & Infrastructure

• 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, containerized applications, and supporting production workloads in regulated, sovereign, government, or isolated cloud environments.

• Experience presenting technical solutions to customer executives, architects, and engineering teams

API & Integration Skills

• Experience integrating LLM services and APIs into enterprise applications and business workflows.
• Familiarity with AI development frameworks and tooling such as LangChain, LlamaIndex, LiteLLM, OpenAI-compatible APIs, and agent frameworks.
• Understanding of API management, authentication and authorization, token management, rate limiting, observability, and monitoring practices.

Performance Engineering, Troubleshooting & Operations

• Experience analyzing and optimizing AI workload performance, including throughput, latency, concurrency, capacity planning, token consumption, and request lifecycle behavior.
• Ability to diagnose and resolve issues across application, model, networking, infrastructure, and operational layers.
• Experience using monitoring, observability, and operational analytics tools to support performance improvement, root cause analysis, and production operations.
• Strong analytical, problem-solving, and cross-functional collaboration skills in complex technical environments.

Preferred Qualifications

• 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.

Critical Success Traits

• Exceptional customer-facing communication skills.
• Ability to bridge business objectives and technical implementation.
• Comfortable operating in ambiguous, fast-moving environments.
• Strong ownership mindset and bias toward action.
• Ability to influence without direct authority across multiple organizations.
• Capable of balancing customer advocacy with technical realism.
• Skilled at expectation management and executive communication.
• Trusted advisor mentality with a focus on long-term customer success.

What Success Looks Like

• Customers successfully deploy and operationalize LLM solutions in OCI environments.
• Customer expectations are aligned with model capabilities and operational realities.
• Production systems achieve agreed-upon performance, reliability, and scalability targets.
• Technical risks are identified early and mitigated proactively.
• Oracle engineering teams receive actionable feedback that improves products and customer outcomes.
• Customers view Oracle as a strategic AI partner and trusted advisor.

Come Join Us!

#LI-PA4

Career Level - IC4