Top Artificial Intelligence Jobs in the Philippines

Conduct quality control reviews of calls, emails, and transactions for compliance with internal standards, Know Your Customer requirements, and regulations. Analyze quality data to identify root causes, recommend process improvements, and implement automation to improve efficiency. Apply foundational AI knowledge, coach colleagues, communicate findings, and collaborate cross-functionally to strengthen quality and operational performance.

Execute and reconcile daily trading activities from order entry through settlement, resolve discrepancies, prepare management reports, and ensure regulatory and policy compliance. The role drives automation, continuous improvement, stakeholder communication, and operational efficiency across trading services. It also supports strategic discussions, manages projects, and mentors junior team members while maintaining knowledge of financial markets and trading systems.

Lead payment lifecycle operations, including daily processing, reconciliations, investigations, exception management, and performance tracking. Resolve control and production breaks, manage operational risk, support fraud prevention, and escalate threats or delays. Partner with stakeholders on automation, process improvements, and client experience enhancements while translating business priorities into execution plans and measurable outcomes.

Reviews and generates cloud compliance and audit reports, applying cloud governance and PCI knowledge. The role also expects proactive adoption of AI and familiarity with at least one cloud service provider.

Supports global indirect tax compliance by preparing VAT and sales tax returns, compiling financial records, researching tax technology, improving order-to-cash processes, identifying tax opportunities and risks, assisting with audits, and monitoring regulatory changes. Collaborates with Accounting, Accounts Receivable, Accounts Payable, Collections, Legal, and the Indirect Tax team.

Performs entry-level data analysis, reporting, dashboard maintenance, and business intelligence support. Prepares, cleanses, validates, and blends data from multiple sources; builds recurring reports and visualizations; conducts basic analyses to identify trends, risks, and opportunities; and communicates actionable insights to stakeholders. The role also supports data quality, governance, documentation, testing, process improvement, and responsible use of AI-enabled analytics tools under the guidance of senior analysts.

Maintains, optimizes, and supports enterprise applications and infrastructure. Troubleshoots application issues, implements software deployments and configuration changes, supports onboarding and decommissioning, and contributes to systems recovery. Configures packaged software, develops modification and interface requirements, coordinates solutions with technical teams and vendors, executes change requests, mentors junior staff, and provides strategic recommendations.

Lead the AI Quality engineering team while remaining hands-on building evaluation infrastructure, observability tooling, diagnostic systems, datasets, annotation workflows, and CI/CD pipelines for production AI agents. Run experiments across prompts, models, routing, caching, and agent harnesses to improve quality, latency, and cost. Partner with AI Core engineering and manage technical direction and team priorities.

Architects, develops, deploys, and maintains enterprise AI/ML solutions using NLP, OCR, RAG, and cloud-native platforms. The role modernizes fax and telephony workflows, mentors engineers, collaborates with product and development teams, solves complex problems, and ensures secure, scalable delivery. Responsibilities include model training, deployment, monitoring, MLOps/LLMOps practices, production support, and designing AI-driven automation.

Develop and maintain complex data pipelines, APIs, statistical models, and advanced analytics solutions for commercial insurance and risk consulting. Use Python, PySpark, SQL, Databricks, AI, machine learning, and predictive modeling to produce data-backed consulting outputs and support new product development. The role also involves researching client risk areas, preparing recommendations, and consulting with senior colleagues on financial and statistical analyses.

Owns the strategy, roadmap, governance, adoption, and measurable outcomes for an enterprise data domain. Translates business needs into trusted, reusable data products and partners with business, architecture, engineering, and governance teams to deliver capabilities. Responsibilities include defining data standards, managing backlogs and priorities, validating quality through business-process testing, supporting analytics and AI use cases, coordinating global delivery, and resolving ownership, quality, and prioritization issues.

Leads a fraud operations team in a player-coach capacity, managing schedules, coaching analysts, handling escalations, and ensuring work quality and compliance. Monitors operational metrics, maintains fraud procedures, improves workflows, develops dashboards, tests new concepts, and partners with compliance and engineering teams to improve detection, efficiency, and customer experience.

Leads global initiatives to optimize and standardize facilities management account operations. Develops SOPs, playbooks, tools, governance processes, performance measures, and training programs; coordinates stakeholders across regions and functions; drives technology adoption, change management, process compliance, and measurable operational improvements. Requires extensive facilities management or operational technology experience, expertise with FM platforms, strong AI and data governance knowledge, and the ability to influence in matrixed organizations.

Leads HR shared-services delivery across countries, teams, queues, and shifts. Oversees case management, SLAs, workforce planning, escalations, compliance, quality, and operational reporting. Manages and develops People Services teams while partnering with HR stakeholders, Payroll, Talent Acquisition, and Centers of Expertise. Drives process improvement, automation, service transitions, governance, change management, and employee-experience enhancements using operational data and customer insights.

Leads enterprise architecture strategy across business, experience, information, application, and technology domains. Defines target architectures, capability maps, roadmaps, reference architectures, and strategic requirements for ERP and enterprise-wide integration initiatives. Advises business and product leaders, evaluates designs, resolves cross-platform dependencies, identifies architectural risks and reuse opportunities, and assesses emerging technologies. Requires strong stakeholder influence, systems thinking, communication, and experience guiding cross-functional teams in complex organizations.

Provides commercial intelligence through market research, lead investigation, CRM data management, pipeline analysis, dashboard development, and pre-sales support. The role uses Excel, Power BI, Power Automate, Salesforce, AI, and automation to generate insights, qualify opportunities, improve data integrity, streamline processes, and support Sales, Marketing, and Commercial Excellence teams.

Supports U.S. indirect tax operations, sales and use tax compliance, exemption data management, audit preparation, and ERP tax configurations. Identifies process bottlenecks and develops Power Platform, AI, RPA, dashboard, and workflow solutions. Coordinates requirements gathering, UAT, defect tracking, documentation, training, and project delivery while collaborating with Tax, Finance, IT, Sales, and Credit stakeholders.

Leads Johnson & Johnson’s Global Services Customer Insights & Analytics capability. The role sets strategy, governance, roadmap, and operating model; manages a multidisciplinary analytics team; translates customer, sales, pricing, contract, market, and operational data into actionable commercial insights; partners with business, finance, IT, and data teams; and measures business value, adoption, productivity, and data quality.

Leads end-to-end front-line risk monitoring analytics using Python, SQL, SAS, cloud technologies, and AI. Designs anomaly detection, metrics, features, visualizations, and scalable monitoring solutions; drives SAS-to-Python modernization and GCP adoption. Establishes analytics standards, automates workflows, ensures explainability and audit readiness, advises business partners, leads projects, and mentors junior team members.

Leads Johnson & Johnson Global Services’ Process Excellence function, overseeing Continuous Improvement and Process Intelligence teams. Develops capability strategy, manages resources and funding, sponsors major transformation projects, maintains the improvement portfolio, quantifies realized value, and embeds a culture of continuous improvement. The role requires Lean Six Sigma expertise, process mining awareness, advanced problem-solving, portfolio management, executive stakeholder influence, and people leadership across global shared-services teams.

Supports information risk governance, cybersecurity oversight, key risk indicators, vulnerability management, control compliance, remediation tracking, and change initiatives. Analyzes data from multiple sources, develops metrics, reports, Power BI dashboards, and presentations, and communicates risks to stakeholders. The role also maintains governance documentation, supports audit readiness, provides guidance on security controls, and identifies automation opportunities, including responsible use of artificial intelligence.

Leads a Customer Success team responsible for customer experience, retention, adoption, and performance metrics. Develops change-management and value-delivery strategies, aligns with renewals and expansion teams, and demonstrates customer ROI. Recruits, mentors, and develops Customer Success Managers while fostering a customer-first culture. Tracks operational metrics, drives cross-functional collaboration, manages escalated client issues, and engages effectively with senior executives.

Develop and maintain complex data pipelines, APIs, statistical models, and advanced analytics solutions for commercial insurance and risk consulting. Use Python, PySpark, SQL, Databricks, AI, machine learning, predictive modeling, and NLP to produce data-backed consulting insights and support new product development. The role also involves risk research, client-oriented solution development, and collaboration with senior stakeholders.

Leads Source-to-Contract procurement operations, including sourcing events, negotiations, contract drafting and execution, stakeholder management, compliance, and SLA delivery. Mentors analysts, drives process improvements, and supports automation and AI initiatives as product owner for S2C tools. Partners with procurement, legal, compliance, IT, and security teams while managing data requirements, privacy controls, and global business relationships.

Collects, processes, and analyzes large datasets to identify trends, insights, and opportunities that improve business performance. Develops KPI reports, dashboards, data models, algorithms, and visualizations; evaluates data integrity; automates reporting; and communicates findings to technical and non-technical stakeholders. Supports analytics, automation, AI, and machine learning initiatives while collaborating with cross-functional teams and senior leadership.