Top Artificial Intelligence Jobs in the Philippines

Design and develop high-performance backend services for an AI-powered trading assistant: build AI agent execution, trading order execution, AI sub-account and API key lifecycle management, integrate Binance trading APIs, implement skills/tool-calling frameworks, and ensure scalable, low-latency real-time data pipelines, observability, and security.

Responsible for functional and API testing of platform products, designing and executing end-to-end tests across frontend, backend, strategy, and algorithms. Validate personalized user experiences, improve test coverage and QA processes, and drive adoption of AI-assisted test generation and automation. Collaborate with Product, Engineering, Algorithm, and Strategy teams to identify issues and ensure quality.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Design, build, and deploy AI and ML solutions across the full lifecycle: data preparation, feature engineering, model training, validation, optimization, and production monitoring. Collaborate with AI leads and cross-functional teams, support onshore/offshore delivery, ensure security and compliance, contribute shared components, and mentor teammates on AI tools and best practices.

Design and deploy AI/ML models and automation to improve procurement analytics, integrate data from ERP and BI tools, build dashboards, lead digital projects, and drive stakeholder adoption and training.

Lead identification, prototyping, and deployment of high-impact AI use cases; integrate AI into systems and workflows; drive adoption via training, playbooks, and change management; establish usage guardrails; partner with IT, Sales Ops, and transformation teams to scale AI capability.

Design, develop, and deploy Generative AI/LLM chatbots, agentic AI, and end-to-end RPA workflows (Power Automate). Integrate APIs and systems, produce technical documentation, run testing and DevOps deployments, lead process discovery, manage automation projects, and support continuous improvement and change management.

Provide frontline operational support for the Compass AI platform: monitor platform health, triage incidents in ServiceNow, perform first-level troubleshooting, assist with content/configuration updates, execute test cases and smoke tests, document runbooks and incident trends, and escalate complex issues to developers and tech leads to maintain platform stability and availability.

Define and monitor AI performance metrics, build dashboards, evaluate AI outputs for accuracy and hallucinations, run A/B experiments, diagnose issues with engineers, connect intent data to outcomes, and present regular performance reviews and QA frameworks to leadership.

Design and own end-to-end AI agent architectures and orchestration for support experiences. Define prompting, persona, escalation/handoff logic, RAG integrations, governance, and evaluation frameworks. Collaborate with engineers, knowledge leads, and PMs to implement, test, and iterate conversational AI solutions aligned to customer experience and compliance.

Support business and platform teams with systems analysis, data collection and organization, gap analysis against an AI operating model, and preparation of structured inputs for AI projects. Research AI tools, document integrations and workflows, assist with quality checks, and help produce analysis, reporting, and project documentation.

Lead and build Knowledge Engineering and AI/Agentforce teams to define AI-driven support strategy, structure knowledge for AI retrieval, govern AI agent behavior, drive adoption, measure performance, and coordinate cross-functional initiatives with product, engineering, and support stakeholders.

Build, deploy, and iterate AI agents and RAG pipelines connecting LLMs to knowledge bases. Integrate agents with CRM/support platforms, debug AI failures, run evaluations, write maintainable code, and collaborate with architects and knowledge engineers.

Use AI-assisted tools like ChatGPT to produce high-volume, conversion-focused, SEO-optimized content (blogs, landing pages, emails). Refine AI drafts, maintain brand voice and factual accuracy, meet ambitious production goals, collaborate with marketing on keyword strategy, and continuously improve AI prompts and workflows to boost engagement and conversions.

Architect and operate sales systems: deploy AI prospecting agents, build automated data-enrichment and scraping pipelines, manage HubSpot CRM architecture and lead routing, run outbound automation, integrate partner workflows, and deliver reporting and SOPs to scale sales operations.

Analyze manual, repetitive processes and build permanent automations using Python, advanced Excel, SQL, and AI/workflow platforms. Create data pipelines, dashboards, and documented solutions that reduce manual effort, improve reporting accuracy, and enable teams to operate without ongoing manual intervention.

Define and track AI feature success metrics, design and analyze experiments (A/B tests), build AI prototypes, explore data to inform product decisions, create dashboards, improve model interpretability and fairness, and collaborate with product and engineering teams to align models with product goals.

Design and implement scalable data and AI solutions. Build and optimize EL(T) pipelines, manage data extraction/integration/storage, apply software engineering best practices, mentor team members, collaborate with stakeholders, and drive AI/data platform adoption across projects.

Design and prototype AI-powered automations and multi-modal conversational agents, build integrated low-code/code workflows, run POC/MVPs, demonstrate solutions to clients, gather feedback, and collaborate on internal AI innovation.

As a Senior AI Engineer, you'll design and deliver scalable AI solutions, lead LLM integration, and mentor engineers while ensuring performance, reliability, and quality compliance.

The AI-Enhanced Virtual Assistant will support AI integration, administrative tasks, communication management, project coordination, and client interaction to enhance operational efficiency.

The Data and AI Success Manager will drive the adoption and implementation of Data and AI solutions, guide customers, and collaborate with teams to enhance business value through data-driven insights and strategies while ensuring compliance with data regulations.

As an AI Image Generation Specialist, you'll enhance and generate images using Photoshop and AI tools while editing photos for global clients and supporting Snappr's growth.

The SEO Manager drives search strategy and execution, focusing on keyword research, content optimization, technical SEO, and performance insights. They collaborate with teams to integrate SEO into content planning and track performance metrics, ensuring alignment with business objectives while supporting AI-related initiatives.

This role involves identifying business opportunities, translating needs into technology solutions, and implementing transformation initiatives using SAP and AI.