Description

You will design and deploy ML models and AI agents to automate IT operations, connector health monitoring, and incident resolution.

This role is on-site.

Responsibilities

• Build and maintain ML pipelines for anomaly detection, predictive failure analysis, and time-series forecasting.
• Integrate LLM APIs (AWS Bedrock, OpenAI, Claude) into orchestration workflows and build RAG pipelines for documentation search.
• Develop agentic AI systems using LangChain or CrewAI for autonomous incident triage and connector lifecycle management.
• Implement NLP-based log parsing, event correlation, and semantic classification to accelerate L4 support.
• Deploy and manage AI inference endpoints on AWS (Lambda, ECS, SageMaker) with proper security and observability.

Required Skills

• 7+ years of hands-on experience in ML engineering, AI application development, or data science.
• Strong proficiency with AWS AI/ML services including SageMaker, Bedrock, Comprehend, Forecast, and OpenSearch.
• Experience building LLM applications, RAG pipelines, and prompt engineering strategies.
• Knowledge of AIOps, ITSM, and IT operations analytics.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
• Proficiency in containerization and orchestration with Docker and Kubernetes.
• Experience with test automation frameworks like Selenium or Playwright.

Preferred Skills

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or Software Engineering.

Key Skills

Education

Bachelor's or Master's degrees