Jobs at Premium Human Resource Solution Limited

Job Summary

• The QA & Application Support Engineer is responsible for ensuring the quality, reliability, and stability of all digital products and applications within the organization.
• The role combines structured quality assurance practices with responsive application support, serving as a critical bridge between product development and the end-user community to deliver a seamless digital experience.

Key Responsibilities

• Design, develop, and execute comprehensive test plans, test cases, and test scripts (functional, regression, integration, performance, and UAT) for all digital products.
• Implement and maintain automated testing frameworks using tools such as Selenium, Playwright, Cypress, Postman/Newman, or equivalent.
• Perform API testing, database validation, and end-to-end workflow testing across web and mobile platforms.
• Log, track, and verify defects using issue-tracking tools (Jira, Azure DevOps); liaise with developers to ensure timely resolution.
• Establish and enforce QA standards, testing methodologies, and quality metrics across the Digital Solutions team.
• Participate in Agile ceremonies (sprint planning, stand-ups, retrospectives) as the quality representative.
• Provide first and second-line application support: triage, diagnose, and resolve incidents escalated from end-users and the helpdesk.
• Monitor application health, performance, and availability using observability tools (Datadog, New Relic, Grafana, or similar); proactively identify and escalate anomalies.
• Maintain and update user support documentation, incident logs, and knowledge-base articles.
• Conduct root cause analysis (RCA) for production incidents and present findings with corrective action recommendations.
• Collaborate with the Technical Writer to document known issues, workarounds, and system limitations.
• Support application rollouts, patches, and version upgrades by coordinating testing and cutover activities.
• Gather user feedback post-release and translate insights into defect reports or product improvement recommendations.

Qualifications & Experience

• Bachelor's Degree in Computer Science, Information Technology, Software Engineering, or a related field.
• Minimum 3 years of combined experience in software quality assurance and application support roles.
• Proven experience writing and executing test cases for web applications, APIs, and mobile platforms.
• Hands-on experience with automation testing tools: Selenium, Playwright, Cypress, or equivalent.
• Proficiency with API testing tools: Postman, REST Assured, or SoapUI.
• Experience with issue tracking and project management tools: Jira, Azure DevOps, or equivalent.
• Basic to intermediate SQL skills for database verification and data validation.
• Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) and integrating test automation.
• Understanding of software development methodologies (Agile/Scrum) and SDLC best practices.
• ISTQB Foundation certification is an advantage.
• Experience with monitoring/observability platforms (Datadog, Grafana, Kibana) is a plus.

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Role Summary

• The Multimedia Producer will spearhead the creation of compelling, high-quality digital content that supports the company's internal communications, product launches, training programmes, and external brand presence.
• The role demands a creative professional who is equally adept at storytelling, technical production, and digital distribution - translating complex ideas into visually engaging multimedia experiences across video, animation, graphic design, and interactive formats.

Key Responsibilities

• Conceptualise, script, produce, and edit video content including corporate explainers, product demos, training videos, executive interviews, and event coverage.
• Design and animate 2D/3D motion graphics, infographics, and visual assets for digital platforms, presentations, and reports.
• Develop and maintain the Group's brand visual identity standards across all multimedia outputs, ensuring consistency and professionalism.
• Produce interactive e-learning modules and instructional content in collaboration with the Technical Writer and Digital Solutions team.
• Manage the full production workflow: pre-production planning, storyboarding, shoot coordination, post-production editing, and final delivery.
• Operate and maintain production equipment including cameras, lighting rigs, audio gear, and studio setups.
• Create and optimise digital content for multiple channels: corporate intranet, website, LinkedIn, YouTube, and internal communications platforms.
• Design visually compelling presentation decks, dashboards, and data visualisation assets for executive and client-facing use.
• Collaborate with the QA team to produce software walkthrough videos, screencasts, and tutorial content for product documentation.
• Manage the digital asset library (DAM system), ensuring all media assets are organised, versioned, and accessible.
• Research and implement emerging multimedia technologies including interactive video, AR overlays, and AI-assisted content generation.
• Brief and manage external creative vendors, freelancers, and production houses where required.
• Track content performance metrics and report on engagement and reach across digital channels.

Qualifications and Experience

• Bachelor's Degree in Mass Communication, Film/Media Production, Graphic Design, Visual Arts, or a related creative field.
• Minimum 4 years of professional experience in multimedia production within a corporate, agency, or broadcasting environment.
• Expert-level proficiency in video editing software: Adobe Premiere Pro, DaVinci Resolve, or Final Cut Pro.
• Strong command of motion graphics and animation tools: Adobe After Effects, Cinema 4D, or Blender.
• Proficiency in graphic design tools: Adobe Photoshop, Illustrator, InDesign, and Figma.
• Experience producing e-learning content using Articulate Storyline, Rise 360, or equivalent platforms is an advantage.
• Demonstrable portfolio of corporate video, motion graphics, and graphic design work.
• Knowledge of colour grading, audio mixing, and post-production workflows.
• Understanding of digital platform optimisation for web, social media, and internal communications systems.
• Experience with AI-assisted content generation tools (generative image, video, or voice synthesis) is a plus.
• Strong project management skills with the ability to handle multiple productions simultaneously under deadline pressure.

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Role Summary

• The Technical Writer will create, maintain, and continuously improve the documentation ecosystem for the Group's digital products, internal systems, and technology processes.
• The ideal candidate will translate highly complex technical information into clear, concise, and user-friendly content, ensuring that internal teams, clients, and external stakeholders can effectively understand and utilise the Group's technology assets.

Key Responsibilities

• Produce high-quality technical documentation including user manuals, API references, system architecture documents, process guides, SOPs, release notes, and FAQs
• Collaborate closely with engineers, product managers, QA specialists, and subject matter experts to gather information and validate accuracy
• Develop and maintain a documentation style guide and information architecture standards for the Digital Solutions department
• Write clear, structured API documentation OpenAPI/Swagger and developer guides to support internal and external integrations
• Create engaging training materials, e-learning content, and quick-reference cards to facilitate user onboarding and adoption
• Manage documentation repositories Confluence, Notion, SharePoint, or equivalent, ensuring content is current, versioned, and easily discoverable
• Produce and maintain knowledge-base articles for the helpdesk and IT support teams, reducing resolution times
• Review and edit technical content produced by engineering teams for clarity, grammar, style, and consistency
• Gather feedback from end-users and stakeholders to iteratively improve documentation quality and usability
• Support change management initiatives by producing communication materials for new system rollouts and upgrades
• Coordinate with the Multimedia Producer to develop instructional video scripts, screencasts, and visual documentation assets
• Ensure all documentation meets regulatory, audit, and compliance requirements where applicable.

Qualifications & Experience

• Bachelor’s Degree in English, Mass Communication, Computer Science, Information Technology, or a related field
• Minimum of 3 years’ experience as a Technical Writer, preferably within a technology, engineering, or digital services environment
• Demonstrable portfolio of technical documentation including API documentation, user guides, SOPs, and release notes
• Strong proficiency with documentation tools such as Confluence, Notion, ReadMe, MadCap Flare, or similar
• Working knowledge of at least one programming or scripting language such as Python, JavaScript, or Bash
• Familiarity with API documentation standards including OpenAPI/Swagger and Postman collections
• Excellent command of English grammar, style, and technical writing conventions
• Experience with version control systems such as Git or GitHub for managing documentation-as-code is an advantage
• Ability to produce basic diagrams and process flows using tools such as Lucidchart, draw.io, or Visio
• Knowledge of documentation-as-code frameworks such as Docusaurus or MkDocs is an added advantage.

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Role Summary

• The Applied AI Engineer will design, build, and operationalise artificial intelligence and machine learning solutions that create measurable business value across the Group's operations.
• The role demands a practitioner who can bridge cutting-edge AI research and real-world product deployment — from data ingestion and model development to production monitoring and continuous improvement.

Key Responsibilities

• Design and implement end-to-end AI/ML pipelines, covering data collection, preprocessing, feature engineering, model training, evaluation, and deployment.
• Develop and fine-tune large language models (LLMs) and generative AI applications tailored to internal business processes, including document intelligence, predictive maintenance, and workflow automation.
• Build and maintain Retrieval-Augmented Generation (RAG) systems, vector databases, and embedding pipelines for enterprise knowledge management.
• Integrate AI capabilities into existing products and platforms via RESTful APIs, microservices, and cloud-native architectures.
• Establish and enforce MLOps best practices: version control for models (MLflow, DVC), CI/CD for ML pipelines, and automated retraining triggers.
• Monitor model performance in production; detect and mitigate data/model drift, bias, and reliability issues.
• Collaborate with the Technical Product Manager and business stakeholders to identify and scope AI use cases with clear ROI.
• Conduct rigorous experimentation (A/B testing, hypothesis testing) to validate model improvements.
• Prepare technical documentation, model cards, and explainability reports for both engineering and non-technical audiences.
• Stay abreast of the latest AI research, frameworks, and tools; champion responsible and ethical AI practices within the organisation.
• Support data engineering efforts including ETL pipeline design, data warehouse integration, and data quality assurance.
• Mentor junior team members and contribute to the Group's internal AI capability-building programmes.
• Support the Head of Digital Solutions in budget planning and vendor procurement processes.

Qualifications and Experience

• Bachelor's or Master's Degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related quantitative field.
• Minimum 3 years of hands-on experience building and deploying production-grade ML/AI systems.
• Strong proficiency in Python; experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Practical experience with LLMs (OpenAI, Anthropic Claude, Mistral, LLaMA) and prompt engineering techniques.
• Familiarity with vector stores (Pinecone, Weaviate, ChromaDB) and RAG architectures.
• Experience with cloud ML platforms: AWS SageMaker, Azure ML, or Google Vertex AI.
• Solid understanding of MLOps tools: MLflow, Kubeflow, DVC, or equivalent.
• Knowledge of SQL and NoSQL databases; experience with data pipeline tools (Apache Airflow, dbt, Spark) is an advantage.
• Understanding of containerisation (Docker, Kubernetes) and cloud-native deployment.
• Strong statistical foundations: probability, hypothesis testing, regression, classification, and clustering.
• Demonstrated ability to communicate model insights to non-technical stakeholders.