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 industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall 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.

Primary Responsibilities

- 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.

Skills & Requirements

- 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.