Top Artificial Intelligence Jobs in the Philippines

Own the full enterprise sales cycle for AI-driven forecasting and optimization solutions, from pipeline generation through closing and customer partnership. Sell to senior executives across supply chain, manufacturing, CPG, retail, and logistics organizations. Build relationships, quantify ROI, manage complex multi-stakeholder deals, close six- and seven-figure contracts, maintain CRM accuracy, forecast reliably, and help shape the company’s sales playbook and go-to-market strategy.

Leads customer-facing applied AI engagements by understanding operational challenges, framing business problems, delivering technical demos, and building Python- and SQL-based prototypes. Supports enterprise sales cycles, evaluations, pilots, implementations, and customer deployments. Requires strong data science and machine learning knowledge, business intuition, project management, and the ability to communicate with technical and non-technical stakeholders.

Supports engineering solution design, process improvement, inspections, standards development, product and solution development, and bid proposal responses. Coordinates subcontractors and suppliers, contributes to project management, evaluates engineering outcomes, and applies technical, commercial, risk, regulatory, and safety knowledge. The role also involves requirements analysis, testing, implementation, reporting, negotiation, and ongoing professional development under the guidance of senior colleagues.

Supports engineering and sales activities by designing process and product solutions, conducting feasibility testing and inspections, preparing bids and proposals, coordinating suppliers and subcontractors, managing project schedules, and addressing technical requirements. The role also contributes to engineering standards, contract management, risk management, customer needs analysis, solution implementation, and continuous improvement while providing technical guidance and collaborating with internal and external stakeholders.

Own the firm’s workforce planning function, oversee Workday data quality, build workforce and capacity models, and analyze the effects of offshoring and automation. Partner with senior leaders to translate workforce strategy into actionable plans, define KPIs, and improve data accuracy. Lead and mentor onshore and offshore teams while identifying automation and AI opportunities. The role requires periodic travel, hybrid work after an initial fully onsite period, and a night-shift schedule.

Perform legal data collection, evaluation, and annotation for AI-powered contract management platforms in Simplified Chinese. Analyze clauses, obligations, and terms in international business contracts; participate in onboarding, calibration, and quality reviews; and collaborate within secure client environments. Requires contract or legal expertise, strong legal interpretation and contract-review skills, and fluency in English and Simplified Chinese. Prior data annotation or machine learning evaluation experience is preferred.

Develop predictive and prescriptive analytics, machine learning models, and data models for semiconductor manufacturing. Analyze production, quality, process, and equipment data to improve yield, productivity, and operational efficiency. Collaborate with manufacturing engineers and stakeholders, support smart manufacturing initiatives, and communicate insights to technical and business audiences.

Executes process discovery, mapping, analysis, and redesign across assigned business domains. The role documents target-state processes, identifies inefficiencies, applies lean improvement methods, prepares automation-ready process specifications, and ensures alignment with enterprise BPM standards, governance, regulatory, audit, and risk requirements. It collaborates with business and IT stakeholders, monitors performance metrics, and supports continuous improvement and automation initiatives.

Conducts process discovery, mapping, analysis, and redesign across assigned business domains. The role develops BPM-compliant target-state processes, identifies inefficiencies, prepares documentation, supports automation-readiness assessments, incorporates compliance requirements, and monitors performance improvements. It collaborates with business stakeholders, IT teams, the Process Architect, and the Automation & AI COE to deliver scalable, optimized processes.

Build and ship end-to-end product features across React frontends and Django backends. Design data models, RESTful APIs, responsive user interfaces, and algorithmic or AI-driven logic involving scoring, ranking, and decision rules. Optimize performance through efficient queries and caching, write production-ready code, and work independently with a distributed startup team. Experience with GCP, Redis, Docker, Kubernetes, React Native, or AI coding assistants is advantageous.

Provides administrative and virtual assistant support while improving business productivity through AI and automation. Responsibilities include managing communications, calendars, files, CRM processes, research, and reporting; identifying repetitive workflows; creating and troubleshooting automations; developing prompts, SOPs, and documentation; training team members; and recommending process improvements. The role supports leadership and cross-functional teams while managing AI tools, business applications, and operational projects.

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.

Investigate and resolve global B2B customer issues involving orders, pricing, billing, deliveries, returns, credits, disputes, and Order-to-Cash processes. Communicate in English and Spanish, identify root causes, coordinate with Supply Chain, Logistics, Finance, Sales, and Customer Operations teams, and improve customer experiences using Lean, Six Sigma, analytics, automation, and AI-enabled tools.

Defines and monitors process performance metrics, establishes baselines, analyzes post-standardization and automation results, and develops dashboards for leadership. The role assesses process stability and automation readiness, validates benefits with Finance and process owners, identifies performance risks, and provides data-driven insights to support continuous improvement, BPM certification, and automation and AI initiatives.

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.

Support AI implementation, Microsoft 365 Copilot deployment, workflow automation, system integrations, and AI tool optimization. Provide training and guidance, assist with human oversight and quality control, and help businesses improve efficiency through AI-enabled processes.

Leads enterprise clinical denial management programs, including strategy, governance, financial performance, reimbursement optimization, denial prevention, client and executive management, transformation initiatives, compliance, and organizational leadership. Oversees multiple teams of at least 50 professionals while partnering with clinical, revenue cycle, coding, finance, and technology stakeholders to improve recovery, prevent denials, and reduce revenue leakage.

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.

Lead design, build, and productionization of GenAI solutions and traditional full-stack applications. Scope use cases, engage stakeholders, mentor developers, manage roadmaps, ensure security/compliance, and operate deployed systems with continuous improvement.

The Engineer II will develop and enhance RPA solutions, troubleshoot issues, collaborate on projects, integrate AI capabilities, and create documentation.