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Job description
Location: Chennai, India
You’ll help reduce repetitive operational work by identifying tasks that can be automated, building safe AI-assisted workflows, and improving how teams detect, diagnose, and prevent incidents. You’ll also help grow the team’s practical AI capabilities.
**Identify and prioritize repetitive production-support tasks** that can be simplified or automated, focusing on activities that consume significant team time or create avoidable manual effort.
**Design, develop, test, and maintain operational automations** for tasks such as health checks, data validation, ticket enrichment, incident summaries, and approved routine remediation.
**Build AI-assisted workflows** for incident triage, knowledge retrieval, runbook guidance, alert correlation, and remediation recommendations.
**Apply agentic AI patterns** to automate multi-step operational workflows, using clearly defined permissions, boundaries, approval steps, and fallback behavior.
**Use predictive analytics and anomaly detection** to identify operational patterns, anticipate potential issues, and trigger timely alerts or automated actions.
**Integrate automation and AI solutions** with approved monitoring, ticketing, knowledge-management, and Supply Chain systems through APIs and other supported interfaces.
**Implement safeguards and quality controls** including testing, access management, audit logging, output validation, human review, and safe failure handling.
**Measure and improve automation outcomes** by tracking time saved, manual effort reduced, accuracy, adoption, failure rates, and operational impact; document solutions and share reusable patterns with the team.
Education: Bachelor’s or master’s degree in computer science, Engineering, Maths or Science
Performed any modern NLP/LLM courses/open competitions is also welcomed.
**Technical Requirements:**
**Agentic AI workflows:** **Design multi-step AI-agent workflows with tool calling, state management, guardrails, human approvals, and fallback handling.**
**Python scripting:** **Build and test maintainable Python automations using tools such as pytest and Ruff.**
**Workflow automation:** **Automate repetitive operations using scripts, REST APIs, webhooks, and workflow orchestration tools.**
**GenAI and RAG:** **Integrate LLMs with prompts, approved knowledge sources, retrieval-augmented generation, and output evaluation.**
**Data and predictive analytics:** **Use SQL, pandas, and scikit-learn to analyze operational data and develop anomaly-detection or forecasting solutions.**
**Observability:** **Use monitoring, logging, and tracing tools to support automation; f**
**Security and quality:** **Apply least-privilege access, secure credential handling, audit logging, automated testing, and safe failure controls.**
**CI/CD and deployments:** **Configure Git-based pipelines for automated testing, deployment, approvals, and rollback.**
**Cloud fundamentals: Understand cloud services, identity and access management, networking, storage, compute, and cloud security.**
**Containers and infrastructure:** **Deploy and troubleshoot containerized workloads using Docker; Kubernetes or Terraform experience is preferred.**
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
Questions you may be asked
What is the difference between mutable and immutable types in Python?
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