DevOps Engineer (RPA)

Our client is a leading innovator in contact center automation, delivering a patented RPA platform used by top organizations in financial services, telecom, insurance, and healthcare. Their platform powers over 1 billion automated actions annually, improving efficiency, reducing costs, and enhancing customer experience.

The company is currently evolving its engineering practices with a strong focus on AI-driven development, enabling faster delivery, higher quality, and greater consistency across its SaaS platform.

• 5+ years of experience in DevOps, SRE, or platform engineering
• Strong experience with CI/CD pipelines (Jenkins, Harness)
• Experience with Docker and Kubernetes
• Experience working with AWS
• Programming or scripting experience (Python, Java, or Bash)
• Experience with repository and artifact management tools (e.g., Bitbucket, Nexus)
• English proficiency at B1+ level or higher

Nice to have:

• Experience with AI-assisted development tools
• Familiarity with test automation tools (e.g., Playwright, Rest Assured)
• Understanding of specification-driven development approaches
• Familiarity with integration patterns or platforms

AI-PDLC Platform Engineering:

• Design and implement end-to-end pipelines (spec → code → test → deploy)
• Build and maintain CI/CD systems using Jenkins, Harness, Helm, and Ansible
• Implement GitOps-based deployment strategies

AI Agent Engineering:

• Develop and manage AI agents that convert EARS specifications into tests, automation, and code validation
• Integrate Claude Code, AWS Kiro, and other AI tools into development workflows
• Improve agent accuracy, performance, and lifecycle management

Quality & Governance:

• Embed SonarQube, Veracode, and CodeRabbit into pipelines
• Ensure full traceability from requirements → code → tests → deployment
• Automate negative testing and edge-case validation

Pipeline Development & Containerization:

• Design and implement Jenkins pipelines that automatically containerize applications during build using Docker
• Create containerized testing environments with mock ingress and egress configurations
• Integrate RestAssured and Playwright within containerized environments
• Develop IaC solutions for consistent and repeatable deployment environments
• Integrate Bitbucket, Nexus, Sourcebot, and Dremio
• Manage secure connectivity and data flows across systems

Reliability & Observability:

• Implement observability using logs, metrics, and tracing
• Improve pipeline performance, scalability, and reliability
• Reduce operational toil through automation

Governance & Leadership:

• Contribute to defining AI-PDLC standards and guardrails
• Participate in the AI-PDLC Steering Committee
• Establish best practices for agent lifecycle management and evaluation
• Drive continuous improvement in quality, cycle time, and automation