AI ML Ops Engineer

About Us

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.

Role

• We are seeking a seasoned AI/ML Engineer to join our Cloud Operations (CloudOps) team. The ideal candidate should have strong expertise in designing, developing, and deploying AI/ML models and automation solutions that optimize cloud infrastructure management and operational efficiency.
  
  

• Design, develop, and deploy machine learning models and AI algorithms to automate cloud infrastructure, monitoring, fault detection, and predictive maintenance.
• Collaborate with Cloud Engineers, ML Engineers, Data Scientists, and DevOps teams to to integrate AI/ML solutions into cloud orchestration and management platforms.
• Build scalable data pipelines and workflows using cloud-native services (preferably AWS, GCP) for real-time and batch ML model training and inference.
• Analyze large volumes of cloud telemetry data (logs, metrics, traces) to extract actionable insights using statistical methods and ML techniques.
• Implement anomaly detection, capacity forecasting, resource optimization, and automated remediation solutions.
• Develop APIs and microservices to expose AI/ML capabilities for CloudOps automation.
• Work with SecOps to ensure ML models comply with privacy, and governance standards.
• Optimize existing AI/ML workflows for cost, performance, and accuracy.
• Stay updated with the latest trends in AI/ML, cloud computing, and infrastructure automation.
  
  

• 6+ years of professional experience in AI/ML engineering, preferably in cloud infrastructure or operations environments.
• Strong proficiency in Python (relevant libraries such as pandas and numpy) or R, or similar programming languages used in AI/ML development.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or similar.
• Hands-on experience with MCP Server, AI Agents, and A2A (Agent-to-Agent) communication
• Experience with Large Language Model (LLM) operations (LLM Ops)
• Expertise in cloud platforms (AWS, Azure, or GCP) and their AI/ML services (e.g., SageMaker, Bedrock, Anthropic, Azure ML, OpenAI, Vertex AI).
• Strong understanding of data structures, algorithms, and statistical modeling.
• Experience building and maintaining data pipelines using tools like Apache Spark, Kafka, Airflow, or cloud-native alternatives.
• Knowledge of containerization and orchestration (Docker, Kubernetes) to deploy ML models in production.
• Familiarity with infrastructure monitoring tools (Prometheus, Grafana, ELK Stack) and cloud management platforms.
• Experience with CI/CD pipelines and automation tools in cloud environments.
• Excellent problem-solving skills and ability to work independently as well as in cross-functional teams.
• Strong communication skills for collaborating with technical and non-technical stakeholders.
• Knowledge of Infrastructure as Code (IaC) tools like Terraform, CloudFormation.
• Experience with cybersecurity principles related to cloud and AI/ML systems.