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• Develop and maintain automated test scripts for web applications across lifecycle and transformation projects
• Coordinate technical quality assurance activities with internal, onshore, and nearshore development teams

AI-driven vulnerability management. When frontier models can generate thousands of findings in a weekend, the bottleneck shifts from discovery to triage, verification, and remediation. We're building the pipeline that makes this sustainable....

• Learn and use groundbreaking technologies.
• Engineers will apply advanced troubleshooting techniques to provide unique solutions for our customers and lead customer interactions by thoughtfully working with them to dive deep into the issue and get the root cause.

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• Lead SAP implementation projects
• Lead SAP migration projects
• Lead SAP rollout projects
• Lead SAP transformation projects
• Manage full project lifecycle from initiation through go-live and hypercare
• Define project scope, objectives, timelines, budgets, and resource plans

• Analyse, evaluate, and refine business requirements, and support the creation of functional specifications
• Design solution plans, including creating mockups where applicable
• Develop dashboards and reports integrated with various business systems and data sources

• Design and assess technical solutions to support seamless customer journeys and high-quality digital experiences.
• Develop clean, maintainable and efficient code for scalable customer-facing applications and platforms.

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Define and drive the ML technical roadmap in alignment with company objectives

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Design and develop interactive 3D, XR, and digital twin applications
• Create immersive visualization experiences for industrial, engineering, facility, and enterprise use cases
• Collaborate with 3D artists, designers, software developers, and engineering teams to build high-quality digital environments

• Lead, mentor, and support a team of full stack developers, building a collaborative and inclusive team environment
• Provide technical direction, guidance, and best practice standards across development, design, and user experience

• Build and evolve CI infrastructure that validates performance methodologies across cloud, on-prem, and hardware targets
• Design controlled, reproducible test environments that help distinguish real regressions from environmental noise when running and profiling targeted workloads

• Design and evolve end-to-end architecture across data ingestion, processing, storage, and delivery
• Define scalable data pipelines and batch or near real-time workflows
• Establish efficient data models, storage strategies, and access patterns

• Definition and driving of the Quality Engineering strategy
• Design, creation and maintenance of reusable test automation frameworks
• Establishment of testing standards and best practices
• Introduction and improvement of CI/CD quality gates
• Building of E2E, integration and API testing capabilities

• Provide Tier 1 helpdesk support for DSV Employee Central (DSV’s Global HRIS that is powered by SAP SuccessFactors).
• Manually update employee data in large scale.
• Helps maintain data integrity in systems by creating reports and analysing data.

• Design, build, review, test, and maintain Ruby on Rails features and services in line with Diligent’s agile engineering practices
• Own technical delivery for projects, epics, and major user stories, including solution design, implementation planning, and execution through to production

• Ensure the quality of data across various domains (Security, Portfolio, Counterparty, Ratings, Benchmark, Analytics, Pricing) and within relevant systems.
• Perform assigned daily/monthly processes, escalating issues or determining solutions to remove obstacles for the team.

• Manage a team of software engineers (typically 5–10 people)
• Handle hiring, onboarding, performance reviews, and day-to-day support
• Keep the team productive, focused, and unblocked
• Support engineers in their technical and career growth
• Own delivery of features and improvements from planning to release