Top Artificial Intelligence Jobs in Caloocan

Build and deploy production AI automations across accounting, compliance, sales, marketing, HR, and finance. The role covers discovery, coding, deployment, monitoring, debugging, support, ROI measurement, and business handover. The engineer will develop LLM-based systems, integrations, agents, and workflows using Python, APIs, databases, warehouses, and business tools. They will partner with non-technical stakeholders, independently own systems end to end, train business users, maintain infrastructure, and identify high-value automation opportunities.

Design and build production-grade generative AI systems, including LLM architectures, fine-tuning pipelines, RAG systems, model evaluations, and multi-agent integrations. Optimize models for latency, throughput, token efficiency, reliability, and cost. Deploy secure enterprise solutions on AWS, implement monitoring and guardrails, translate client requirements into model strategies, and contribute production-quality code, design reviews, and reusable engineering practices.

Perform image segmentation and object labeling using polygons, bounding boxes, and semantic segmentation. Annotate datasets involving roads, vehicles, satellite imagery, blueprints, and roofing while meeting accuracy and productivity targets. Follow QA guidelines, collaborate with team leads to resolve unclear tasks, and suggest workflow improvements. The role includes structured remote training and is suitable for candidates with basic computer skills and no prior annotation experience.

Leads the strategy, development, and delivery of AI, machine learning, and generative AI solutions across healthcare domains. Responsibilities include designing scalable software, integrating LLMs and agentic AI, maintaining code quality and production operations, collaborating with stakeholders, mentoring engineers, and leading AI/ML teams. The role requires expertise in modern ML frameworks, cloud platforms, DevOps, CI/CD, NLP, model evaluation, prompt engineering, and production-grade AI applications.

Generate qualified sales opportunities for AI and B2B SaaS clients through outbound calling, email, LinkedIn outreach, and social selling. Responsibilities include lead qualification, market research, meeting and demo scheduling, CRM and pipeline management, prospect follow-up, sales collaboration, and achieving activity and opportunity KPIs. The role requires strong SaaS sales knowledge, executive communication, objection handling, organization, and independent remote work capabilities.

Supports finance transformation and operational excellence initiatives through process improvement, automation, data analysis, documentation, stakeholder management, governance, and change management. Applies Lean, Six Sigma, DMAIC, PDCA, Design Thinking, BPMN, AI, Power BI, Power Automate, and Alteryx to improve efficiency, accuracy, productivity, timeliness, controls, and costs. Advises operations leaders, tracks project benefits, and promotes continuous improvement across Global Business Services.

Analyzes structured and unstructured data, develops and deploys predictive and machine learning models, designs experiments, creates dashboards, ensures data quality, and communicates insights to technical and business stakeholders. Senior-level candidates may lead analytical initiatives, mentor junior staff, and influence strategic decisions.

Lead ecommerce retouching for still-life and on-figure fashion imagery, ensuring color accuracy, product integrity, and premium brand standards. Guide two retouchers, review offshore partner work, and collaborate with photographers, art directors, and content operations. Develop AI imaging prompts, evaluate generated outputs, identify appropriate AI use cases, and help create scalable workflows combining automation, offshore production, and internal editing.

Design and deliver secure, scalable AI solutions for clients, from discovery and architecture through implementation, governance, adoption, monitoring, and optimization. Lead workshops, identify use cases, guide proofs of concept, integrate AI with enterprise systems and workflows, and provide technical leadership. Translate business needs into production-ready architectures while ensuring responsible AI, quality, security, and measurable business outcomes.

Build and deploy AI agents and process automation solutions using Microsoft Copilot Studio and Power Platform. Develop prompts, conversation flows, integrations, and knowledge-grounding approaches; support testing, deployment, monitoring, troubleshooting, and optimization. Collaborate with stakeholders to translate business requirements into practical solutions, create reusable components, and promote responsible AI adoption.

Designs, develops, and deploys AI agents and process automation solutions using Microsoft Copilot Studio and the Microsoft ecosystem. Translates business needs into scalable solutions, develops integrations, designs prompting and knowledge-retrieval approaches, and supports testing, deployment, monitoring, and continuous improvement. Collaborates with stakeholders, promotes responsible AI adoption, contributes reusable solution standards, and evaluates emerging AI capabilities.

Provides senior-level technical support and escalation management for AI-enabled and enterprise applications. Troubleshoots authentication, authorization, integrations, APIs, data retrieval, user interfaces, AI response quality, prompt execution, and MCP-related issues. Performs root cause analysis, coordinates cross-functional resolutions, manages incidents within SLAs, supports customers and internal users, creates knowledge documentation, contributes to AI adoption and operational improvements, and mentors support colleagues.

Partner with cross-functional business stakeholders to identify workflow pain points and redesign processes using AI-native applications and autonomous agents. Build and deploy AI solutions integrated with Salesforce, NetSuite, and Workday, while translating business needs into intuitive technology experiences. The role requires strong business acumen, LLM prompting proficiency, foundational agent-development knowledge, systems fluency, clear communication, and comfort working through ambiguity.

Bridges business needs and AI solutions by gathering requirements, assessing AI and automation opportunities, developing business cases, supporting solution design and delivery, facilitating stakeholder collaboration, assisting testing and implementation, and tracking project outcomes, benefits, reports, and continuous improvement initiatives.

Leads operational oversight for AI-powered products and platforms, monitoring performance, developing dashboards, analyzing business outcomes, and driving process improvement. The role supports AI governance, risk management, compliance, operational standards, forecasting, and scalable operating models. It also partners with engineering, product, and business stakeholders to deliver operational excellence and present strategic recommendations.

Leads the strategy, roadmap, delivery, and continuous improvement of AI-powered products. Defines product vision, requirements, priorities, metrics, and success criteria while collaborating with executives, engineering, AI, data science, and business teams. Oversees product launches, adoption, performance optimization, stakeholder communication, and responsible AI governance. Requires strong product management, analytical, commercial, Agile, executive communication, and cross-functional leadership skills.

Supports responsible AI governance through framework development, risk and impact assessments, fairness and transparency reviews, regulatory compliance, documentation, stakeholder advisory, training, and continuous improvement. The role collaborates with technical, legal, compliance, risk, and business teams to promote ethical, accountable, and trustworthy AI adoption.

Supports the day-to-day operation, monitoring, reporting, governance, and continuous improvement of AI-powered platforms. Analyzes performance metrics, identifies operational issues and optimization opportunities, develops dashboards and reports, maintains procedures and documentation, and coordinates issue resolution across AI engineers, product teams, operations leaders, and business stakeholders. The role also supports AI adoption, compliance, risk mitigation, and operational standards.

Evaluates AI chatbot functionality, response quality, accuracy, compliance, and conversational effectiveness. Executes test plans, regression testing, and user acceptance testing; documents defects and test results; analyzes conversation flows and recurring issues; collaborates with AI trainers, prompt engineers, and development teams; prepares performance reports; and supports chatbot optimization, testing standards, and evaluation framework improvements.

Supports digital marketing, brand, and lead-generation activities through branded content creation, social media management, Meta advertising support, campaign monitoring, and basic reporting. Responds to and qualifies prospective clients by phone, gathers relevant information, and routes qualified leads to the appropriate team. Works remotely from Manila with an Australian team while managing deadlines, stakeholders, brand standards, and marketing workflows independently.

Designs and manages AI-powered workflows, administrative automations, SOPs, reminders, reporting systems, and process controls. The role identifies inefficiencies, builds reliable systems using AI and automation platforms, documents processes, monitors recurring operations, closes follow-up loops, trains team members, and partners with the Admin Manager to improve administrative performance and accountability.

Build and scale customer-facing and internal web applications for an AI-powered eCommerce customer service platform. Develop and enhance AI agents, integrate eCommerce platforms, apply privacy and security practices, and help shape the product’s technical direction. As the founding technology team member, the role offers significant ownership, equity, and potential progression into technical leadership.

Build and deploy production software powered by AI, LLMs, agentic architectures, and intelligent automation. Develop scalable services, APIs, workflows, copilots, RAG systems, and decision-support platforms using React, Node.js, TypeScript, and Python. Operationalize statistical and AI models, evaluate foundation models, optimize performance and cost, monitor production systems, and collaborate with technical and business teams to deliver maintainable solutions.

Designs and maintains enterprise full-stack applications using Azure, .NET, and Node.js. Integrates Azure AI and machine learning services, develops databases, pipelines, and APIs, and implements CI/CD, testing, DevOps, security, and compliance practices. Collaborates on technical solutions, participates in design and code reviews, troubleshoots production issues, and provides Level 3 application support.

Oversee portfolios of Generative AI data operations projects, managing delivery, capacity planning, vendors, budgets, quality, risks, automation, and client reporting. Coach project managers and coordinators, collaborate with recruiting and finance, enforce data security and compliance, and improve processes across distributed teams.