Jobs at SKO SYSTEMS INDIA PVT LTD

Design, develop, deploy, and maintain scalable enterprise applications using C# and .NET technologies. Own application modules across the development lifecycle, contribute to architecture, troubleshoot complex issues, optimize performance, conduct code reviews, and maintain automated testing and CI/CD pipelines. Collaborate with product, QA, UI/UX, and DevOps teams, document technical solutions, mentor junior developers, and integrate cloud, AI, and automation services into enterprise applications.

Perform manual and automated testing across web, mobile, APIs, and databases. Design test plans and reusable automation frameworks, validate functionality and data, manage defects, analyze failures, and execute regression suites through CI/CD pipelines. Collaborate with Agile development, product, business analysis, and DevOps teams throughout the SDLC. Use programming, SQL, reporting, version control, and AI-assisted tools to support reliable software releases.

Leads a cross-functional software delivery POD as business analyst, Scrum Master, project manager, and client point of contact. Responsibilities include requirements elicitation, process analysis, backlog management, sprint facilitation, estimation, release planning, scope and risk control, UAT, quality governance, client reporting, impediment removal, and team development. The role is accountable for delivering agreed scope on time, within quality standards and commercial terms.

Owns full-cycle recruitment from sourcing through offer acceptance for technical and non-technical roles. Uses job boards, LinkedIn, referrals, campus channels, ATS/HRMS platforms, and AI-assisted screening tools to build pipelines and conduct first-round evaluations. Coordinates interviews, communicates with candidates, manages offers and pre-employment checks, tracks recruiting metrics, maintains candidate records, and hands accepted hires to the HR Manager for onboarding.

Supports CI/CD pipelines, cloud environments, automated builds and deployments, monitoring, logging, troubleshooting, documentation, and incident response. Collaborates with development, QA, Data Science, and MLOps teams to deploy and monitor applications and machine learning models. Assists with AIOps integration, infrastructure automation, ticket resolution, rollbacks, and maintaining standard operating procedures while developing DevOps expertise.

Supports AI initiatives through research, framework evaluation, dataset preparation, model training experiments, hyperparameter tuning, and evaluation. Documents technical risks and feasibility findings while contributing to responsible AI practices, knowledge sharing, and collaborative development using Python, PyTorch or TensorFlow, Git, Jupyter, and Linux.