AI Solutions Engineer

CyberOne

. Run discovery sessions with business and technical teams .

Posted 9/24/2026full-timeRemote • PhilippinesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing AI applications and automation workflows, integrating systems, and translating business needs into technical solutions. Proficient in designing and implementing reusable AI architectures and best practices while ensuring effective stakeholder communication and collaboration.

Highest-signal resume keywords

AI Application DevelopmentSolution Design and ArchitectureAPI IntegrationPrototyping and IterationStakeholder Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI PlatformsAutomation WorkflowsApplication IntegrationBusiness Process AnalysisTechnical Requirements TranslationRapid PrototypingWorkflow OrchestrationCI/CDAI Security and Governance

Soft Skills

Stakeholder CommunicationConsulting SkillsIndependent Work

Tools & Technologies

AzureAWSGCPWorkflow Automation PlatformsAgent Frameworks

Industry Keywords

AI SolutionsEnterprise System IntegrationHuman-in-the-Loop ControlsMonitoring and EvaluationRAGEmbeddingsVector SearchEnterprise Knowledge RetrievalPrompt EngineeringContext Engineering

Tech Stack

Tools & technologies

AWSAzureGoogle Cloud Platform

About the role

Key responsibilities & impact

Run discovery sessions with business and technical teams
Map existing processes, systems, pain points, and manual activities
Identify and prioritise opportunities for AI and automation
Challenge existing processes and design improved future-state workflows
Translate business problems into technical requirements and solution designs
Build prototypes and proofs of concept
Develop AI applications, agents, and automation workflows
Integrate AI solutions with existing systems, APIs, and data sources
Integrate disparate systems to automate workflows and remove manual effort
Design human-in-the-loop controls, guardrails, and monitoring
Test solutions and measure effectiveness against defined business outcomes
Take successful prototypes through to production
Support teams with adoption and new ways of working
Establish reusable AI architecture, engineering patterns, and best practices
Contribute to the longer-term internal AI and automation roadmap
Build AI systems, agents, automation, support assistants, workflow automation, and AI capabilities embedded in existing applications as opportunities arise

Requirements

What you’ll need

Strong software engineering experience; programming language is flexible
Hands-on experience building applications using a variety of AI platforms
Experience building AI agents, tool-calling workflows, or deterministic automation
Experience integrating applications with APIs, databases, and external systems
Ability to understand and analyse business processes
Strong solution design and architecture skills
Experience translating ambiguous business problems into practical technical solutions
Ability to prototype rapidly and iterate based on user feedback
Strong stakeholder communication and consulting skills
Comfortable working independently in a greenfield environment
Useful experience with agent and workflow orchestration frameworks
Useful experience with RAG, embeddings, vector search, and enterprise knowledge retrieval
Useful experience with evaluation and monitoring of LLM applications
Useful experience with prompt and context engineering
Useful experience with Azure, AWS, or GCP
Useful experience with workflow and automation platforms
Useful experience with enterprise system integrations
Useful experience with AI security, permissions, governance, and guardrails
Useful experience with CI/CD and production deployment of AI applications

Benefits

Comp & perks

No specific benefits or compensation extras stated