Jobs at Temus

Analyze client business challenges, elicit and document requirements, evaluate system and data product capabilities, recommend solutions, and support testing, implementation, training, go-live, and application support. The role also contributes to business analysis planning, governance deliverables, stakeholder communications, risk and issue tracking, and coordination between business and technology teams.

Supports PMO and project delivery by tracking progress, KPIs, risks, issues, milestones, and outcomes. Coordinates stakeholders, produces status reports, supports governance, and drives continuous improvement across projects. The role requires program management, analytical, communication, negotiation, and problem-solving skills, with occasional weekend go-live and extended-hours support.

Drive end-to-end digital transformation programmes by framing client problems, designing and prototyping solutions, translating needs into delivery plans, supporting agile execution, and enabling adoption. The role involves AI-enabled workflows, operating model and organisational change, stakeholder facilitation, responsible AI governance, capability building, and coaching across business and technology teams.

Design, build, automate, and operate secure, scalable cloud platforms across AWS, Azure, or GCP. Develop Infrastructure as Code, Kubernetes platforms, CI/CD pipelines, automation, cloud networking, security controls, monitoring, and reliability solutions. Troubleshoot incidents, optimize performance and costs, integrate testing and security scanning, and guide development teams on DevOps practices. Collaborate with architects, engineers, security teams, and clients to deliver resilient cloud-native environments.

Leads end-to-end digital transformation engagements, framing ambiguous problems, designing AI-enabled solutions, managing delivery, driving organizational adoption, and advising senior stakeholders. Oversees cross-functional teams, workshops, prototyping, agile delivery, change strategies, responsible AI practices, and capability building. Coaches junior consultants and develops reusable delivery playbooks. Requires strong consulting, transformation, operating model, stakeholder management, AI fluency, and structured problem-solving experience.

Lead the design and production delivery of enterprise AI solutions, combining hands-on AI engineering with technical architecture and multidisciplinary team leadership. The role covers LLMs, agentic tooling, cloud-native AI platforms, software architecture, data engineering, DevOps, responsible AI, and stakeholder collaboration across enterprise and public-sector environments.

Develop and maintain full-lifecycle web and mobile applications using Java, AEM, and related cloud technologies. Responsibilities include requirements gathering, solution design, development, release management, post-launch maintenance, issue resolution, and collaboration with Product, Design, Business, and agile delivery teams. The role also supports project managers and Scrum Masters in stakeholder consultation and delivery. Candidates may work across full-stack development, DevOps, cloud infrastructure, databases, microservices, and platform technologies.

Works with clients to identify business problems, gather and analyze requirements, and define effective solutions. Responsibilities include functional design, workflow analysis, user stories, feasibility assessment, UAT planning and execution, end-user training, delivery clarification, and post-production verification. The role requires collaboration with technical delivery teams throughout the development lifecycle and supports consulting or IT system implementation projects.

The Software Quality Engineer develops and maintains automated testing frameworks, integrates tests into CI/CD pipelines, and executes functional, regression, exploratory, integration, UAT, performance, and security testing. The role defines risk-based test strategies, manages defects and test repositories, improves agile testing practices, and collaborates with product, business, engineering, and system stakeholders to ensure reliable software delivery.

Lead the design and delivery of enterprise-scale data platforms and pipelines, using modern data platforms, processing frameworks, streaming technologies, and cloud services. Build, lead, and mentor a data engineering team; support client relationships, proposals, migrations, governance, security, and compliance. Contribute technical thought leadership through blogs and community engagement while delivering solutions from proof of concept through commercialization.

Supports the Head of Corporate Affairs with executive meeting coordination, briefs, action tracking, growth and partnership research, account and partner materials, and AI thought-leadership content. Produces intelligence digests, presentations, proposals, executive narratives, and client-facing communications while maintaining trackers and editorial calendars. Requires strong research, writing, organization, presentation, commercial judgment, discretion, and interest in enterprise AI.

Drive end-to-end digital transformation by framing problems, designing AI-enabled solutions, prototyping, delivering via agile teams, and driving adoption and change through stakeholder engagement, training, and governance.

Lead multiple small teams to deliver end-to-end Newgen-based solutions. Design, implement, integrate, and maintain enterprise software; perform code reviews, POCs, testing, client coordination, risk analysis, and documentation to ensure compliant, high-performance deployments.

Temus is hosting a Consulting Info Day to showcase its consulting practice in digital transformation. Attendees will hear from consultants about roles and opportunities, and receive registration details by email. Event is on 17 Sep 2025 at Temus Office, Singapore.

Lead AI Engineer will design and deploy advanced AI and agentic LLM systems, lead and mentor an AI/data engineering team, build MLOps pipelines and cloud deployments, produce client proposals and technical thought leadership, and drive model lifecycle, evaluation, and responsible-AI practices.

The Director of Data will lead a team of data engineers, manage the P&L of the Data practice, and ensure effective collaboration across teams to drive data solutions.

Design, build, and operationalise large-scale cloud data pipelines (batch and streaming) using Databricks/Snowflake and cloud platforms to support reporting, automated systems and AI/ML teams. Administer cloud data platforms, optimise SQL/storage, implement CI/CD, IaC, containerisation and serverless solutions, and collaborate with clients, partners and internal teams to scale data engineering deployments.

Plans, leads, and documents software projects across the SDLC, translating business needs into requirements and user stories. Manages project execution, testing, stakeholders, vendors, timelines, quality, and costs. Evaluates solutions, addresses client concerns, and coaches junior team members while ensuring project requirements are met.

Design, build, deploy and govern AI solutions (LLMs, agentic systems, MLOps). Collaborate with clients and partners, deliver end-to-end AI projects, and continuously upskill in AI engineering and deployment best practices.

Support consulting teams by conducting primary and secondary research, analyzing data, synthesizing findings, producing clear written outputs and presentations, communicating with stakeholders, and contributing to project delivery in a team environment.