Senior AI Ops Engineer

Overview

Lead AI/ML solutions to automate and optimize enterprise IT operations.

Key Responsibilities

• ai automation
• ai integration
• data governance
• model monitoring
• security controls
• llm optimization

Tasks

-Automate critical processes, including anomaly detection, root cause analysis, and resolution workflows leveraging advanced AI/ML and/or GenAI technology. -Lead collaboration with IT and DevOps teams to integrate AI tools into cloud and on-premise use case solutions across multiple environments. -Ensure compliance with data governance and regulatory requirements across cloud environments -Monitor and troubleshoot production deployments to ensure model accuracy, latency, and uptime requirements are met. -Research, recommend and implement the latest advancements in AI/ML technologies to maintain a cutting-edge IT infrastructure (i.e., newly developed Large Language Models, Agentic frameworks, OCR tooling, advanced Chunking & Embedding methodologies) -Support projects as a trusted technical advisor to team members to solve complex technical challenges. -Implement robust security controls for AI/ML workflows, including data encryption, IAM policies, and secure API integrations. -Leverage artificial intelligence (AI) and machine learning (ML) technologies and frameworks to drive greater observability and service operations automation. -Align AI Ops initiatives with broader organizational goals and long-term IT strategies. Optimize LLM performance, scalability, and cost-efficiency using techniques like model pruning, quantization, or distributed inference. -Drive the interpretation and translation of enterprise goals into technical specifications, delivering a point of view on cloud agnostic technologies. -Architect and deploy advanced AI/ML solutions to monitor, analyze, and optimize IT operations. -Establish, maintain, and improve data pipelines to support performance of AI and GenAI solution applications. -Own, develop and maintain process to support IT Operations Management, Discovery, Monitoring, and AIOps solutions using current industry platforms.

Requirements

• python
• kubernetes
• aws
• ci/cd
• nlp
• master's

What You Bring

-Strong analytical, strategic thinking, and leadership skills. Excellent communication and collaboration abilities to work effectively with stakeholders across all levels. -Strong knowledge of database systems (SQL and NoSQL) Position -Experience building CI/CD pipelines for machine learning and experience with tools like GitLab CI/CD or Jenkins for automating workflows. -Experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs Advanced skills in Natural Language Processing, including summarization, translation, and augmentation (preferred experience with advanced prompting and/or model fine tuning) -Experience with automated alerting and logging best practices for large-scale AI systems. -Familiarity with DevOps principles, CI/CD pipelines, and ITIL best practices. Strong experience in Programming/scripting languages (e.g., Python, Pyspark, etc.) ETL pipelines, data lakes, and data warehousing -Advanced proficiency in scripting and programming languages (e.g., Python, Bash, PowerShell). -Must be willing to work out of an office located in Bangalore India. -Experience with Infrastructure-as-Code (IaC) tools like Terraform, Ansible, or CloudFormation. -Proven ability to lead and deliver AI solutions in large-scale IT environments. Experience working with BMC Observability and AIOps technologies for monitoring Cloudbased environments (AWS, Azure, Google Cloud Platform) and their key technologies. -Familiarity with tools like Kubeflow, MLflow, Airflow, or Argo Workflows. -Proficiency in GPU/TPU acceleration and parallelization techniques. Familiarity with performance tuning, auto-scaling, and load balancing for high-throughput AI workloads. -7+ years of experience in IT operations, DevOps, or AI/ML systems implementation. Expertise in one or more of the following is desirable: DevOps, Serverless, Networking, Security, Storage, Databases, IOT, AI/ML, Cloud Migration and IT Transformation. -Experience orchestrating the entire AI/ML lifecycle (data ingestion, model training, validation, deployment, monitoring). -Deep knowledge of AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and algorithms. -Proven proficiency with tools like Apache Spark, Kafka, Snowflake, Redshift. -Proficiency in Kubernetes, Docker, and container orchestration. -Expertise in IT monitoring tools (e.g., AWS CloudWatch, Azure Monitoring, Splunk, Dynatrace, Prometheus, Datadog, etc.). -Expertise in cloud platforms like AWS, Azure, or Google Cloud Platform (GCP). -Bachelor’s degree or Master’s degree in computer science, Engineering, or related fields (Master’s degree preferred).

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About Ge Vernova

-Traces roots back to Edison and Alstom, merging power, renewable, digital & financial wings. -Headquartered in Cambridge, MA, crafts large-scale gas turbines, SMRs, wind turbines, hydro and grid tech to fuel economies. -On the nuclear front, advancing small modular reactors (like BWRX‑300) in partnership with utilities and supporting semiconductor projects. -Wind prowess spans onshore, offshore and blade making—with key sites like Dogger Bank offshore and blade plants in Spain. -Electrification arm tackles grid stability: HVDC, transformers, storage, conversion, plus GridOS software powering smarter infrastructure. -Weaves finance and consulting through energy-infrastructure investments, funding solar farms to pipelines via GE Energy Financial Services.

Sector Specialisms