Overview

Experience: 10+ Years (Min 6 years of AWS devops enterprise level experience)

Location: Bangalore (Onsite)

Uan and linkedin is mandate

Contract - 6 months plus

NOTE- Please make sure that candidate should have all the required skills.

Key Responsibilities

• Design, build, and manage AWS cloud infrastructure.
• Develop and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or similar tools.
• Automate infrastructure provisioning using Terraform or CloudFormation.
• Manage Kubernetes (EKS) and Docker-based container platforms.
• Implement Infrastructure as Code (IaC) best practices.
• Configure monitoring and logging solutions using CloudWatch, Prometheus, Grafana, ELK, or Datadog.
• Automate deployments using scripting (Python/Bash).
• Implement security best practices, IAM, Secrets Manager, and cloud governance.
• Troubleshoot production issues and optimize application availability and performance.
• Collaborate with development, infrastructure, and security teams.

Required Skills

• AWS (EC2, VPC, IAM, S3, RDS, EKS, ECS, Lambda, Route 53, CloudWatch)
• Terraform / CloudFormation
• Kubernetes (EKS)
• Docker
• Jenkins / GitHub Actions / GitLab CI
• Linux Administration
• Python / Bash Scripting
• Git
• Monitoring & Logging (CloudWatch, Prometheus, Grafana, ELK, Datadog)
• DevSecOps knowledge

Preferred Certifications

• AWS Solutions Architect – Associate/Professional
• AWS DevOps Engineer – Professional
• Kubernetes (CKA/CKAD)

AI Solution Architect

UAN and linkedin Is mandate

Location- Gurgaon

Experience- 10-15 Years

Role Purpose

Design and implement AI-enabled payroll automation solutions leveraging Generative AI, Machine Learning, Intelligent Automation, and enterprise integration technologies to improve payroll efficiency, accuracy, and employee experience.

Key Responsibilities

• Define AI strategy for payroll automation.
• Design scalable AI solution architecture.
• Identify AI use cases such as payroll validation, chatbot, anomaly detection, and document intelligence.
• Select appropriate AI models and cloud services.
• Define AI governance, security, and responsible AI practices.
• Design integrations between AI services and enterprise HR applications.
• Guide development teams on AI implementation.
• Evaluate emerging AI technologies.

Technical Skills

• Generative AI
• Azure OpenAI
• AWS Bedrock
• LLMs
• NLP
• Machine Learning
• Python
• LangChain
• Vector Databases
• REST APIs

Functional Skills

• Payroll domain knowledge
• HR processes
• Solution architecture
• Cloud architecture
• Enterprise integration

Experience

10+ years in enterprise architecture

5+ years implementing AI solutions

Preferred Certifications

• Azure AI Engineer
• AWS Machine Learning Specialty
• TOGAF

Tools

• Azure AI, AWS AI Services, OpenAI APIs, Python, Git, Docker

Deliverables

• AI Architecture
• AI Design Documents
• AI Governance Framework
• Integration Architecture

Success Metrics

• AI adoption rate
• Reduction in manual payroll effort
• Payroll accuracy improvement
• AI model performance