Top Artificial Intelligence Jobs in Quezon City

Design and build AI-first mobile apps using FlutterFlow: create user flows, wireframes, interactive prototypes, and production-ready builds. Integrate REST APIs, auth, state management, caching, and custom code; maintain reusable components and scalable design systems. Leverage AI tools across research, ideation, UI generation, testing, and documentation. Collaborate cross-functionally to iterate, optimize usability and accessibility, and deliver polished production-quality mobile experiences.

Lead visual design across product, marketing, education, and business assets using strategic systems thinking and AI-assisted tools. Create brand identity, presentations, reports, landing pages, social assets, and production-ready collateral while ensuring consistency, quality, accessibility, and cross-functional collaboration to improve user understanding and engagement.

Lead multiple concurrent HealthTech, AI education, and eMarketing projects from planning through delivery. Build timelines, manage risks, coordinate cross-functional teams, run event and promotions calendars, optimize workflows using AI, maintain communication and documentation, and drive continuous operational improvement to ensure high-quality launches and stakeholder alignment.

Own the full sales lifecycle for AI-powered products: prospecting, discovery, proposals, negotiation, closing, onboarding, and account growth. Maintain CRM, track pipeline and forecasts, collaborate with marketing/product/operations, and use AI tools to improve productivity and customer outcomes.

Design, build, test, deploy, and optimize advanced GoHighLevel CRM systems, funnels, websites, automations, and AI-powered customer journeys. Collaborate cross-functionally to improve lead routing, sales pipelines, campaign delivery, reporting, and documentation while continuously using AI to enhance workflows, QA, troubleshooting, and system scalability.

Write conversion-focused copy across websites, landing pages, email, ads, product launches, and educational content using AI-assisted workflows. Improve headlines, CTAs, readability, customer messaging, and conversion rates. Collaborate cross-functionally, analyze performance, refine brand voice, and continuously optimize AI-driven content processes.

Coordinate end-to-end digital and live events, manage registrations and speakers, support email and social campaigns, improve attendee experience and community engagement, and leverage AI to optimize planning, content, reporting, and workflows across cross-functional teams.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

Lead AI-enabled process improvement for Source-to-Pay by designing and building AI agents, configuring Coupa Procurement/Sourcing/CLMA modules, testing E2E configurations, tracking defects, collaborating with Coupa and IT teams, and mentoring staff to implement GenAI features and operationalize solutions.

Develop and maintain .NET Core/.NET 6 applications, design APIs and services, integrate AI/LLM capabilities (OpenAI, Anthropic, Azure OpenAI), use AI coding assistants, write tests, follow CI/CD and engineering best practices, and collaborate with product and engineering teams remotely.

Design and implement complex backend services for Binance Square. Collaborate with product, DevOps, and QA to deliver high-quality microservices, promote engineering best practices, and perform code reviews.

Early-career intern will support AI projects for compliance and risk (KYC, KYB, EDD). Tasks include testing and optimizing LLM/Agent workflows, reviewing prompts and model outputs, documenting findings and edge cases, supporting small-scale implementations, and performing operational analysis to improve processes.

Early-career full stack engineer role to build end-to-end product features, integrate AI coding tools into the workflow, mentor peers, improve cross-team efficiency, and contribute across the product lifecycle from design through deployment.

Build and maintain full-stack web applications using React/Vue frontends and Java/Spring Cloud microservices. Design and consume REST/AI model APIs, work with SQL and NoSQL databases, use AI-assisted development tools, own features end-to-end, collaborate across product and design, ensure high-quality UI/UX, write tests, and contribute to documentation and architecture.

Join as an early-career full stack engineer to build frontend and backend product features, integrate AI coding tools into development workflows, translate product requirements into implementations, and grow toward autonomous full stack delivery while improving cross-team processes.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Own post-sale AI customer journey: lead multiple AI implementation projects, manage timelines and risks, coordinate engineering/data teams, drive customer relationships, identify expansion opportunities, and improve delivery processes and playbooks.

Design, develop, fine-tune, deploy, and monitor generative AI and ML models; build data pipelines and integrations; implement automation and agentic systems using tools like LangChain and REST APIs; evaluate emerging AI tools; collaborate with cross-functional teams and mentor junior engineers.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

As a Data Encoder, you'll structure, label, and QA data for training and analytics while meeting quality and throughput targets. This role requires proficiency in AI tools and strong attention to detail.