About Role

We are seeking a skilled Platform Engineer to join our Automation Engineering team. This role combines cloud infrastructure automation, DevOps, and scripting expertise with advanced AI/ML practices, focusing on integrating Generative AI into automation workflows. The ideal candidate will help build scalable frameworks, improve operational efficiency, and support our cloud-first initiatives by leveraging the latest automation and AI-driven technologies.

Roles & Responsibilities

Design cloud automation workflows using Infrastructure-as-Code tools such as Terraform or CloudFormation.
Build scalable frameworks for infrastructure provisioning, deployment, and configuration across multiple cloud platforms.
Develop service catalog components compatible with platforms like Backstage.
Integrate Generative AI models to enhance service catalog functionalities, including automated code generation and validation.
Architect CI/CD pipelines for automated build, test, and deployment processes.
Maintain deployment automation scripts using Python or Bash.
Implement Generative AI models (e.g., RAG, agent-based workflows) for AIOps use cases like anomaly detection and root cause analysis.
Utilize AI/ML tools such as LangChain, Bedrock, Vertex AI, or Azure AI for Generative AI solutions.
Develop and manage vector databases and document sources (Amazon Kendra, OpenSearch, or custom solutions).
Engineer real-time data pipelines to provide operational insights that support AI-driven automation.
Build and manage MLOps pipelines to deploy and monitor Generative AI models, ensuring performance and preventing model decay.
Select and integrate LLM models for specific AIOps workflows.
Collaborate with cross-functional teams to refine automation and AI-driven processes.
Research and adopt emerging tools and technologies to drive scalability and efficiency.

Qualifications Required

Education: Bachelor’s or Master’s in Computer Science, Engineering, or related field.
Experience: 3–8 years in cloud infrastructure automation, DevOps, and scripting.
Must-Have Skills:
- Proficiency with Infrastructure-as-Code tools (Terraform, CloudFormation).
- Strong expertise in Python and generative AI frameworks (RAG, agent-based workflows).
- Knowledge of cloud-based AI services (Bedrock, Vertex AI, Azure AI).
- Familiarity with vector databases (Amazon Kendra, OpenSearch, or custom solutions).
- Competence in data engineering tasks (feature engineering, labeling, real-time streaming).
- Proven track record building and maintaining MLOps pipelines for AI/ML models in production.
Nice to Have:
- Background in Flow Engineering tools (e.g., LangGraph) or workflow orchestration platforms.
- Understanding of end-to-end AIOps processes to refine cloud-based automation solutions.

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