Jobs at Personetics

Own enterprise sales across ASEAN and North Asia, winning and expanding Tier 1 and Tier 2 banking accounts. Manage the full sales cycle from prospecting through contracting, including executive engagement, technical and regulatory reviews, procurement, and legal. Build and defend commercial business cases, coordinate presales and professional services teams, maintain pipeline accuracy, and represent Personetics at regional events. The role is remote-first but requires residence in Singapore or Hong Kong and approximately 30%–40% regional travel.

Own new-business and expansion sales across Tier 1 and Tier 2 banks in ASEAN and North Asia. Build senior stakeholder relationships, develop account strategies, manage complex enterprise software sales cycles through signature, and coordinate presales, professional services, product, and customer success teams. Develop and defend commercial business cases, maintain accurate pipeline forecasts, represent Personetics at industry events, and manage long-term customer partnerships. The role is based in Singapore or Hong Kong and requires approximately 30% to 40% regional travel.

Owns the SaaS and business application portfolio, including administration, integrations, permissions, access governance, vendor management, licensing, and system optimization. Partners with business teams to translate requirements into configurations, workflows, automations, and integrations. Leads AI and agentic AI implementation and governance, while managing regulated-environment controls. Runs multi-stakeholder implementations and migrations from scoping through adoption.

The Senior Product Manager will own the Engage product domain, leading strategy, roadmap, and delivery while managing cross-team dependencies and prioritization.

Lead the company's internal AI strategy, drive AI adoption across departments, build agent platforms and machine-readable knowledge repositories, optimize processes with AI workflows, establish AI governance, security, and FinOps, and enable business units to use AI-assisted development.

Senior technical leader defining and evolving SaaS platform architecture, guiding squads on scalable, reliable designs. Responsibilities include creating architecture artifacts, reviewing designs and code, prototyping, partnering with product, promoting reuse and platform capabilities, driving observability and reliability, and mentoring senior engineers.

Manage a scaled North America portfolio to drive adoption, retention, and measurable outcomes of the Personetics platform using a digital-first, AI-triggered engagement model. Monitor health and usage, run automated check-ins and digital QBRs, design automated workflows for renewals and upsells, coordinate with Product/Engineering/Sales, host webinars and create knowledge-base content, and escalate high-touch accounts as needed to maximize GRR and NRR.

Lead a squad responsible for backend development of business-facing applications, ensuring high-quality solutions, mentoring team members, and driving engineering standards.

Design, implement, and maintain cloud-native infrastructure and CI/CD pipelines. Manage multi-cloud and Kubernetes environments, lead on-premises-to-cloud migrations, ensure production reliability, monitor and troubleshoot systems, and support deployment and operation of AI workloads.

Manage a scaled North America portfolio to drive adoption, retention, and measurable outcomes via AI-driven, digital-first engagement. Monitor health, run automated check-ins and digital QBRs, support renewals/expansion, coordinate cross-functionally, and feed product roadmap with aggregated client insights.

Design, build, and scale a BI data platform and ETL/ELT pipelines (batch and real-time). Own data ingestion, transformation, modeling, storage, observability, lineage, and governance. Integrate tools like Airflow, Databricks, streaming platforms, and BI tools. Collaborate with engineers, analysts, and product managers to enable analytics, reporting, and operational product integrations.

The Backend Engineer will lead technical initiatives, enhance platform capabilities, design scalable systems, and improve engineering processes while collaborating with teams.

Define and evolve the SaaS data architecture across ingestion, ELT, modeling, storage, APIs, governance, and observability. Guide squads, review data models and pipelines, prototype solutions, enforce standards, and ensure scalable, secure, resilient production data systems.