Job Description: AI Engineer – GenAI Platform Automation

Experience: 10+ Years

Location: Remote – Pan India

Employment Type: Haparz Payroll

Work Mode: Remote

Notice Period: Immediate / Short Notice Preferred

About the Role

We are looking for a senior AI Engineer – GenAI Platform Automation to lead automation initiatives across enterprise Generative AI, Data Science, Data Engineering, and Analytics platforms.

The role focuses on building scalable, secure, and self-service automation capabilities across infrastructure provisioning, CI/CD, cloud environments, AI workload deployment, governance, observability, and operational excellence. The ideal candidate will have strong hands-on experience in platform engineering, cloud automation, DevOps, Infrastructure-as-Code, Python, and enterprise GenAI ecosystems.

Key Responsibilities

- Lead end-to-end automation initiatives for enterprise GenAI, Data Science, Data Engineering, Metadata, Data Quality, Event Streaming, and Analytics platforms.
- Design self-service automation for infrastructure provisioning, setting onboarding, deployment, governance, monitoring, and operational workflows.
- Build automation capabilities supporting the AI lifecycle, including experimentation, model training, deployment, inference, observability, and lifecycle management.
- Develop scalable Infrastructure-as-Code solutions using Terraform and cloud-native automation frameworks.
- Design and maintain enterprise CI/CD pipelines, automated testing, deployment, and release processes using modern DevOps toolchains.
- Automate Kubernetes, containers, serverless,



and distributed computing environments in collaboration with cloud and platform engineering teams.
- Develop automation solutions for GenAI and Agentic AI applications, including MCP-enabled services, API integrations, workflow automation, and event-driven architectures.
- Implement observability, monitoring, logging, tracing, alerting, automated remediation, and reliability engineering practices.
- Work with architecture, security, governance, engineering, and business teams to ensure enterprise standards and compliance requirements are met.
- Conduct technical design reviews, automation assessments, code reviews, and establish engineering best practices.
- Provide technical leadership and mentorship to engineering teams adopting automation-first and platform engineering practices.

What We’re Looking For

- 10+ years of hands-on experience in platform engineering, automation engineering, cloud engineering, DevOps, or distributed systems.
- Strong experience building enterprise self-service platforms supporting AI/ML, Data Science, Data Engineering, or Advanced Analytics workloads.
- Strong expertise in automation frameworks, CI/CD, DevOps, Infrastructure-as-Code, and software delivery lifecycle automation.
- Hands-on experience with Terraform and cloud-native infrastructure automation.




- Strong experience with Python for automation, orchestration, scripting, tooling, and platform engineering.
- Experience with Bitbucket, Bamboo, Jira, Confluence, or similar enterprise DevOps toolchains.
- Experience working with Kubernetes, containers, serverless platforms, YARN, and distributed processing environments.
- Knowledge of Generative AI and Agentic AI architectures, MCP frameworks, APIs, workflow automation, and enterprise AI platforms.
- Experience with event-driven architectures and technologies such as Kafka and streaming platforms.
- Strong understanding of cloud engineering, networking, security, scalability, resilience, and cost optimization.
- Experience implementing observability solutions covering monitoring, logging, tracing, alerting, and operational dashboards.
- Understanding of metadata management, data lineage, data governance, and semantic-layer concepts is highly valuable.

Good to Have

- Experience supporting enterprise GenAI platforms, AI governance, model management, and AI operationalization.
- Experience with GitOps, DevSecOps, Platform Engineering, and Reliability Engineering practices.
- Exposure to data governance, data quality, metadata management, and model lifecycle automation.
- Experience creating reusable internal developer platforms and self-service engineering tools at enterprise scale.
- Banking, AML, fraud detection, financial crime, or risk analytics domain experience is an advantage.

Skills:- GenAI,, DevOps, Python, Infrastructure architecture, Infrastructure-as-Code, Terraform, Agentic AI, Platform Engineer and Kafka

📌 Hiring AI Engineer – GenAI Platform Automation (India)
🏢 Haparz
📍 India