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Toku

Toku

toku.co

2 Jobs

123 Employees

About the Company

Toku creates bespoke cloud communications and customer engagement solutions to reimagine customer experiences for enterprises. Recognised as one of LinkedIn's Top Startups and ranked among Singapore and APAC's Fastest Growing Companies by The Straits Times, The Financial Times and Statista, Toku delivers a comprehensive end-to-end solution. The company helps businesses navigate the complexities of global digital transformation and enhance their Customer Experience with mission-critical cloud communication solutions that deeply integrate with customer data and business processes. Toku combines global strategic consulting expertise, bespoke technology, in-country infrastructure, local connectivity and global reach. The business works with organisations as diverse as Singapore Airlines, foodpanda, Gojek, Sony and numerous government agencies to move their communications and customer engagement to the cloud. Whether you are a cloud-based enterprise or just starting your digital transformation journey, Toku has solutions to suit your communications and customer engagement needs.

Listed Jobs

Company background Company brand
Company Name
Toku
Job Title
VP – Network Operations Centre
Job Description
**Job Title:** Vice President, Network Operations Centre (NOC) **Role Summary:** Lead and own a global, 24×7 NOC ensuring 99.99% service availability, SLA compliance, and audit readiness across all platforms. Manage people, processes, and escalation ownership in a distributed follow‑the‑sun model. Focus on operational excellence, customer satisfaction, and continuous improvement rather than hands‑on troubleshooting. **Expectations:** 10–15+ years of senior NOC or service operations leadership; proven ability to meet stringent contractual KPIs (99.99% uptime, sub‑5‑minute critical response, high CSAT); strong people and process management; experience with ITIL‑aligned operations and major incident management. **Key Responsibilities** - Own and drive global NOC operations across Contact Centre, CPaaS, UCaaS, Microsoft Teams routing, and carrier services. - Maintain 99.99% availability and meet all contractual SLA targets; ensure Level‑1 ticket resolution average <30 min. - Serve as senior escalation point for S1/S2 incidents; coordinate decisions, communications, and response within 5 minutes. - Standardise, improve, and enforce SOPs; achieve full operational adoption within 90 days. - Restructure NOC skill mix, upskill teams, and reduce over‑dependence on senior engineers to improve throughput. - Lead audit readiness (ISO, data‑privacy, incident, change management), achieving zero major findings. - Build, mentor, and retain a high‑performing NOC organization; maintain tool and process certification >90 % and keep attrition below industry benchmarks. - Manage geographically distributed teams (India, Philippines, Malaysia, LATAM, etc.) in a disciplined follow‑the‑sun model. - Collaborate with Engineering, Product, and Service Delivery to align operational realities with platform design and roadmap decisions. - Provide data‑driven operational reporting to senior leadership on availability, incidents, SLA performance, risks, and improvement initiatives. - Drive operational change during transition periods without disrupting live services. **Required Skills** - Executive leadership & people management of global, multi‑shift teams. - Deep understanding of NOC operations, incident response, change, and problem management. - Strong KPI ownership and accountability for availability, response times, and customer satisfaction. - Expertise in major incident management and executive communication under pressure. - Proficiency in ITIL framework application and continuous process improvement. - Excellent stakeholder collaboration and cross‑functional partnership skills. - Strategic thinking, data analysis, and reporting capabilities. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Information Technology or related field (or equivalent experience). - ITIL v3/v4 Foundation (or higher) certification; additional ITIL or Six Sigma certifications a plus. - Proven senior NOC leadership experience (10–15+ years) in large‑scale, 24×7 service operations.
Job, France
On site
Senior
26-12-2025
Company background Company brand
Company Name
Toku
Job Title
AI Engineer
Job Description
**Job Title:** AI Engineer **Role Summary:** Design, build, and operate MLOps pipelines and cloud infrastructure to deploy, monitor, and scale AI models for production environments, ensuring reliability, performance, and cost‑efficiency across AWS-based platforms. **Expectations:** - Deliver end‑to‑end AI model lifecycle management at enterprise scale. - Enable applied AI engineers to push models from experimentation to production with minimal friction. - Collaborate cross‑functionally with infrastructure, SRE, and backend teams to align practices with broader system standards. **Key Responsibilities:** - Own and continuously improve MLOps pipelines (training, deployment, versioning, governance). - Build CI/CD workflows for model packaging, versioning, and deployment across multiple environments. - Operate and optimise AWS AI workloads (EC2, ECS, SageMaker, related compute/storage/network components). - Manage GPU‑enabled workloads, addressing scalability, reliability, and cost‑efficiency. - Implement monitoring, alerting, and observability for deployed models (health, performance, stability). - Maintain and evolve shared tooling (MLflow, Docker, deployment frameworks) to enhance developer productivity. - Support live AI services, diagnosing deployment, scaling, and infrastructure issues. - Ensure reproducibility, traceability, and governance throughout the ML lifecycle. **Required Skills:** - Proven MLOps experience building production pipelines for machine learning systems. - Advanced knowledge of AWS services for AI workloads (EC2, ECS, SageMaker, related networking and storage). - Hands‑on Docker and container orchestration for ML deployments. - Experience with experiment tracking and model versioning tools (MLflow or equivalent). - Leadership in GPU workload management (scaling, performance tuning, cost optimisation). - Proficient in Python for ML system integration and automation. - Practical understanding of LLMs, NLP models, and applied ML concepts to support deployment and monitoring. - Production support experience for live ML services with end‑user impact. - Strong collaboration and communication skills across applied AI, backend, and infrastructure teams. **Required Education & Certifications:** - Bachelor’s degree (or higher) in Computer Science, Engineering, Data Science, or a related technical field. - Preferred certifications: AWS Certified Machine Learning – Specialty, or equivalent MLOps/Machine Learning credentials.
Job, France
On site
26-12-2025