Job Description Summary

The Senior AI Ops Engineer is a strategic leader responsible for driving the evolution of IT operations through the innovative application of AI/ML technologies. This role focuses on building and scaling AI-driven systems that
enhance IT infrastructure performance, automate routine tasks, and ensure
system reliability. The Senior AI Ops Engineer collaborates closely with IT
leadership, DevOps teams, and data scientists to design solutions that proactively identify and resolve operational issues, minimize downtime, and
drive efficiency at scale. This role also requires expertise in managing large
datasets, implementing predictive models, and ensuring seamless integration of
AI tools into complex IT environments. You will support enterprise-scale AI
initiatives leveraging Bedrock foundational models, Azure OpenAI, and Google
Gemini. The core platform is based on AWS, with additional integrations into
Azure for specific AI use cases. As a senior member of the team, you will mentor others, contribute to long-term IT strategies, and champion AI adoption across the organization.

As a GE Vernova accelerator, GE Vernova Advanced Research is driving
strategy and leading research & development efforts to execute on the
business’s mission to help power the energy transition. We forge the
collaborations and help invent the technologies required to electrify and
decarbonize for a zero-carbon future.

Representing virtually every major scientific and engineering discipline, our
researchers are collaborating with GE Vernova’s businesses, the U.S.
government, and more than 420 entities at the forefront of technology to execute on 150+ energy-focused projects. Collectively, these research programs and initiatives aim to solve near term technical challenges, deliver next generation product advances, and drive long term breakthrough innovation to enable more affordable, reliable, sustainable, and secure energy.

Job Description

Responsibilities:

• Architect and deploy advanced AI/ML solutions to monitor, analyze, and optimize IT operations.
• 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.
• Establish, maintain, and improve data pipelines to support performance of AI and GenAI solution applications.
• 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)
• Drive the interpretation and translation of enterprise goals into technical specifications, delivering a point of view on cloud agnostic technologies.
• Support projects as a trusted technical advisor to team members to solve complex technical challenges.
• Own, develop and maintain process to support IT Operations Management, Discovery, Monitoring, and AIOps solutions using current industry platforms.
• 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.
• Monitor and troubleshoot production deployments to ensure model accuracy, latency, and uptime requirements are met.
• Implement robust security controls for AI/ML workflows, including data encryption, IAM policies, and secure API integrations.
• Ensure compliance with data governance and regulatory requirements across cloud environments

Key Technical Skills:

• Deep knowledge of AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and algorithms.
• Advanced proficiency in scripting and programming languages (e.g., Python, Bash, PowerShell).
• Experience orchestrating the entire AI/ML lifecycle (data ingestion, model training, validation, deployment, monitoring).
• Familiarity with tools like Kubeflow, MLflow, Airflow, or Argo Workflows.
• Expertise in cloud platforms like AWS, Azure, or Google Cloud Platform (GCP).
• Proficiency in Kubernetes, Docker, and container orchestration.
• 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 Infrastructure-as-Code (IaC) tools like Terraform, Ansible, or CloudFormation.
• Expertise in IT monitoring tools (e.g., AWS CloudWatch, Azure Monitoring, Splunk, Dynatrace, Prometheus, Datadog, etc.).
• Experience with automated alerting and logging best practices for large-scale AI systems.
• Proficiency in GPU/TPU acceleration and parallelization techniques. Familiarity with performance tuning, auto-scaling, and load balancing for high-throughput AI workloads. 
• Experience building CI/CD pipelines for machine learning and experience with tools like GitLab CI/CD or Jenkins for automating workflows.
• 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
• Proven proficiency with tools like Apache Spark, Kafka, Snowflake, Redshift.
• Strong knowledge of database systems (SQL and NoSQL) Position

Requirements:

• Bachelor’s degree or Master’s degree in computer science, Engineering, or related fields (Master’s degree preferred).
• 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.
• 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.
• Strong analytical, strategic thinking, and leadership skills. Excellent communication and collaboration abilities to work effectively with stakeholders across all levels.
• Must be willing to work out of an office located in Bangalore India.  

Additional Information