Total 4 job vacancies by KMS Technology

This Job Description belongs to and is for the One-Day Hiring event only.

KMS One-day Hiring is a fresher recruitment event that offers you an opportunity to interview with KMS and know your employment result within the same day.

Selection Process:

• Apr 20 - 8 Apr: Applications and CV Screening
• May 15: Online Interview and Offering

Your key responsibilities:

• Participate in all software development activities following Scrum process
• Design solutions and approaches for software features or subsystems
• Write high-quality code to implement software features or fix bugs
• Perform unit testing, documentation and all other activities defined in Definition of Done before passing source code to Testing team
• Communicate and report internally or directly to client on status or result of work

This Job Description belongs to and is for the One-Day Hiring event only.

KMS One-day Hiring is a fresher recruitment event that offers you an opportunity to interview with KMS and know your employment result within the same day.

Selection Process:

• Apr 20 - 8 Apr: Applications and CV Screening
• May 15: Online Interview and Offering

Your key responsibilities:

• Develop a strong understanding of domain knowledge and client testing processes to execute testing activities effectively.
• Work closely with the project team on daily tasks and participate in sprint demo meetings with clients.
• Develop, maintain, and execute test cases/test scripts.
• Identify, report, track, and monitor defects using the defect tracking system.
• Prepare and review test documentation to ensure accuracy and completeness.
• Address issues related to testing quality and suggest improvements.
• Communicate test progress, results, and quality risks both internally and directly with the client.

Your key responsibilities:

• Assist in setting up, configuring, and maintaining CI/CD pipelines (e.g., GitHub Actions, GitLab CI/CD, Jenkins).
• Support the implementation of Infrastructure as Code (IaC) using tools such as Terraform or Ansible.
• Help manage cloud infrastructure (AWS, Azure, or GCP) under supervision.
• Assist in monitoring system performance and setting up logging/alerting tools (e.g., Prometheus, Grafana, ELK).
• Collaborate with development and QA teams to improve deployment processes and system reliability.
• Support containerization and orchestration efforts using Docker and Kubernetes.
• Assist in implementing security best practices in deployment and infrastructure.
• Troubleshoot basic system and deployment issues.
• Perform other tasks assigned by the Leader/Manager.

AI-Native Engineering Practice - Technical Ownership:

• Own and continuously evolve KMS's AI-native SDLC operating model at KMS: agent workflow designs, verification gates, context management standards, and eval frameworks

• Build and lead multi-agent systems using orchestration layers such as Claude Code, GitHub Copilot Workspace, Cursor, LangGraph, CrewAI, or equivalent — from prototype to production

• In collaboration with the Director of Engineering, contribute to and help maintain KMS's AI toolchain selection criteria — evaluating tools with engineering rigor, not hype — and publishing internal guidance on when AI helps and when it hurts

• Establish prompt engineering standards, agent evaluation (evals) loops, and AI output quality gates across the delivery organization

Capability & Standards Leadership

• Develop and continuously evolve KMS's AI-native SDLC playbook — standards, workflow templates, case studies, and guardrails that delivery teams can adopt immediately

• Design and lead internal upskilling programs (workshops, pairing) that move engineers from AI-assisted to AI-native working patterns

• Track the AI capability frontier — model improvements, new agent frameworks, emerging risks — and translate signals into timely updates to KMS's practices

Client Delivery

• Work closely alongside KMS Delivery Teams — as an AI transformation advisor and execution partner — identifying the highest-value automation opportunities across the SDLC and coordinating with the team to bring them to life

• Design and deploy agent-orchestrated workflows tailored to each client's stack, team maturity, and delivery context — with measurable ROI

• Build business cases for AI-native adoption with clients and account managers, framing the value in terms of velocity, quality, and cost

• Represent KMS's AI-native engineering capabilities in client conversations, QBRs, and RFP responses — acting as a credible technical authority