PairSoft

SDET

• Design, develop, and maintain automated test frameworks using Selenium, Playwright, and .NET technologies
• Ensure product quality through efficient and scalable automation practices
• Develop and maintain automation frameworks using Selenium and Playwright
• Write automation scripts using C# (.NET)
• Collaborate with Product, QA, and Development teams
• Execute and analyze automated test results
• Integrate automation into CI/CD pipelines
• Perform API testing using Postman or similar tools
• Identify, track, and report defects
• Support release and production validation
• Leverage AI-powered testing tools to enhance automation efficiency
• Utilize self-healing automation techniques
• Assist in AI-based test case generation and optimization
• Analyze defect patterns using AI insights

QA Automation Engineer

Consultant

• Installs and configures PairSoft products and applications in both Cloud and On-Premise environments, ensuring compatibility and performance.
• Provides technical guidance on product prerequisites, system compatibility, and deployment best practices tailored to client environments.
• Assists in identifying and troubleshooting product-related defects, escalating to development or engineering teams when necessary.
• Participates in client meetings and internal project discussions, offering technical input on feasibility, architecture, and integration strategies.
• Identifies opportunities for improving product functionality, integration flow, or deployment methodology and relays structured feedback to internal teams.
• Documents technical implementation approaches, custom workflows, and client-specific configurations to support repeatable best practices.
• Designs, develops, and tests custom configurations, API integrations, and automation workflows within the PairSoft platform and connected systems.
• Supports and maintains active configurations and custom JavaScript modules, monitors logs for performance optimization, and troubleshoots end-user issues.
• Performs other technical consulting or engineering duties as assigned within the scope of Product Services or Professional Services.

Technical Consultant

Cloud Engineer

• Manage, monitor, and support cloud infrastructure and services primarily on AWS
• Assist in cloud transformation and migration activities toward Azure and Oracle Cloud
• Deploy and maintain cloud resources such as compute, storage, networking, and security configurations
• Handle day-to-day operational tasks: incident management, service requests, and root cause analysis
• Support and troubleshoot Windows Server environments including patching and performance tuning
• Configure and troubleshoot IIS for hosting and supporting web applications
• Manage and troubleshoot DNS, Active Directory, and identity/access-related issues
• Support MS SQL Server administration tasks (basic setup, backups, restores, performance checks, connectivity)
• Work with databases: troubleshooting, access management, backup/restore coordination, and monitoring
• Build, run, and troubleshoot Docker containers; support container-based deployments
• Administer and troubleshoot Linux systems (basic services, logs, permissions, networking)
• Create and maintain automation using Shell scripting and PowerShell scripting
• Perform application and infrastructure troubleshooting using logs, monitoring tools, and metrics
• Implement basic security best practices, access controls, and support compliance requirements
• Maintain documentation for configurations, SOPs, and troubleshooting guides
• Collaborate with developers, QA, and security teams to improve stability and performance

CloudOps Engineer

Machine Learning Engineer

• Design, implement, and maintain end-to-end ML pipelines covering training, validation, deployment, monitoring, and retraining — with a focus on production reliability and long-term maintainability.
• Own and operate production ML infrastructure using Infrastructure as Code (IaC), making architectural tradeoffs and enforcing best practices.
• Lead CI/CD practices for ML, including artifact/model versioning, promotion, rollout/rollback, and dev/test/prod parity.
• Deploy and run ML/GenAI workloads on Azure using Azure App Service and Azure Container Apps, with monitoring via Application Insights.
• Implement robust model observability: performance monitoring, data quality checks, drift detection, alerting, and dashboards.
• Drive compute and cost optimization for training and inference (scaling policies, capacity planning, cost/performance tradeoffs).
• Support GenAI operational needs, including LLM inference patterns, embeddings, and retrieval pipelines; enable hooks for evals/guardrails where required.
• Ensure ML systems meet security and governance requirements (RBAC/least privilege, secrets management, audit logging, encryption, secure access patterns).
• Partner with the Data & AI Architect to translate architecture standards into reusable pipeline templates and operational controls.
• Collaborate with and mentor AI engineers; contribute to model development/experimentation as capacity allows.

QA Automation Engineer

Technical Consultant

CloudOps Engineer

Senior MLOps Engineer