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Senior AI Automation Engineer

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Hybrid

Senior AI Automation Engineer

Randstad

Senior AI Automation Engineer

Skills

Google Cloud PlatformTypescriptPythonGolangData AnalysisMachine LearningAIAWSKubernetesNo-code AutomationsSAP ERPSAP SuccessFactorsComplianceJavascriptTerraformAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Hybrid

Published on:

22 September 2026

What they need


Immediate Joiners Only

Senior AI Automation Engineer

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline.
  • 7+ years of experience in enterprise software development, automation engineering, platform engineering, or systems integration.
  • Experience deploying and supporting enterprise automation platforms.
  • Strong understanding of artificial intelligence, machine learning, large language models, and generative AI applications.
  • Experience with prompt engineering and AI workflow design.
  • Strong experience developing and consuming REST APIs.
  • Experience with enterprise systems integration and data orchestration.
  • Hands-on experience with cloud platforms, including Azure, AWS, or GCP.
  • Proficiency in one or more programming languages such as Python, JavaScript, TypeScript, or Go.
  • Experience with workflow automation platforms, identity and access management, enterprise security controls, and monitoring or observability platforms.
  • Excellent communication and stakeholder management skills.

Preferred Qualifications

  • Experience administering or developing solutions on the Serval platform.
  • Experience building AI-native business applications.
  • Experience with retrieval-augmented generation, vector databases, agentic AI frameworks, AI orchestration platforms, LangChain, Semantic Kernel, or Azure AI Services.
  • Experience with Kubernetes and containerized workloads.
  • Familiarity with Terraform and Infrastructure as Code practices.
  • Experience supporting enterprise IT Service Management platforms.
  • Experience in AI governance, AI security, and responsible AI practices.
  • Previous experience working in a fast-paced enterprise transformation environment.

Key Responsibilities

AI Platform Administration & Governance

  • Manage platform configurations, permissions, agent lifecycle management, environments, and governance controls.
  • Develop and maintain standards for AI workflow creation, testing, deployment, security, and operational support.
  • Establish platform monitoring, auditing, usage reporting, and adoption metrics.
  • Ensure AI solutions comply with enterprise security, privacy, compliance, and governance requirements.

AI Workflow & Automation Development

  • Design, develop, deploy, and maintain intelligent AI-powered workflows and agents using the Serval platform.
  • Convert manual and repetitive business processes into scalable automated solutions.
  • Create and optimize prompts, agent behaviors, workflows, and automation logic.
  • Implement process orchestration across enterprise applications and business systems.
  • Evaluate workflow performance and continuously improve effectiveness through feedback and analytics.

Enterprise Integrations

  • Develop and maintain integrations between Serval and enterprise platforms, including Microsoft 365, SuccessFactors, SAP, Entra ID, Azure services, HR systems, security platforms, and internal applications and APIs.
  • Build connectors, APIs, data pipelines, and automation services that enable AI agents to execute business workflows securely and reliably.
  • Troubleshoot integration performance, scalability, and reliability issues.

AI Operations & Continuous Improvement

  • Monitor platform health and AI workflow performance.
  • Analyze outcomes, identify optimization opportunities, and improve automation effectiveness.
  • Participate in AI model evaluation, prompt engineering, testing, and validation.
  • Assist with AI governance reviews and risk assessments.
  • Develop best practices for AI deployment, observability, and operational support.

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