OCI_and_Oracle_Solution_Architect

Overview The primary responsibility of this role is to act as a Forward Deployment Engineer in

medium-to-large opportunities for mid-sized clients; that may involve solutioning including

but not limited to understanding client requirements, deployment planning, environment

configuration, integration design, testing, and go-live execution of AI-native and agentic AI

solutions. Mid-market companies increasingly require rapid deployment of AI capabilities

that can generate measurable business outcomes while integrating seamlessly with existing

technology landscapes. These organizations require scalable, repeatable, and right-sized

deployment approaches that accelerate time-to-value and minimize implementation risk.The role requires the

ability to rapidly configure integrations, validate architecture assumptions, resolve

deployment challenges, and accelerate realization of business value.

As a Forward Deployment Engineer, you will assist sales, delivery, architecture,

engineering, and client teams in deploying AI-native solutions, agentic workflows, and

automation capabilities within client environments. Your goal is to establish trusted

relationships with internal teams and customers while ensuring successful implementation,

rapid adoption, and value realization.

The successful candidate will bring a Forward Deployment Engineering mindset, combining

technical expertise, cloud engineering knowledge, architecture awareness, rapid

prototyping capabilities, and innovation-led thinking to solve complex deployment

challenges and accelerate business outcomes.

Key Responsibilities

Solution Deployment, Integration & Forward Deployment Engineering

Translate deployment requirements into executable implementation plans using deep

knowledge of AI-native solutions, cloud platforms, APIs, and enterprise integrations.

Collaborate with Sales Pursuit, Solution Architects, Engineering, and Delivery Teams to

ensure successful deployment and adoption of AI solutions.

Deploy and configure pre-built agentic AI solutions within client environments while

preserving solution integrity and performance standards.

Act as the technical bridge between architecture, engineering, delivery, and client teams

during implementation activities.

Identify deployment risks and develop mitigation strategies to support successful go

live execution.

Ensure solutions meet security, compliance, scalability, and operational requirements.

Client Environment Integration & Configuration

Adapt integrations, data connections, APIs, and workflows to align with client-specific

technical landscapes.

Deploy AI solutions into AWS and GCP environments while ensuring optimal

performance and reliability.

Configure authentication, access controls, monitoring, and operational support

requirements.

Integrate AI assets with enterprise systems, data platforms, collaboration tools, and

business applications.

Validate deployment readiness through testing, performance assessment, and

environment verification.

Go-Live Execution & Operational Readiness

Lead deployment activities and support rapid go-live execution for AI solutions and

agentic workflows.

Conduct deployment validation, smoke testing, and operational readiness assessments.

Drive issue identification, troubleshooting, and resolution during implementation and

stabilization phases.

Ensure seamless handoff to operations and delivery teams through documentation and

knowledge transfer.

Develop reusable deployment accelerators, templates, and best practices that improve

implementation efficiency.

Client Engagement & Advisory

Establish trusted advisor relationships with client stakeholders, architects, engineers,

and operations teams.

Conduct deployment workshops, technical assessments, and implementation planning

sessions.