Enterprise Reliability Strategist

6 days ago

Thiruvananthapuram, Kerala, India beBeeReliability Full time ₹ 2,00,00,000 - ₹ 4,00,00,000

Transforming modern enterprises requires a strategic approach to reliability.

BugRaid.AI is pioneering the development of an enterprise-ready incident copilot – intelligent systems that can detect, diagnose, and resolve complex production incidents across massive streams of logs, metrics, traces, and alerts.

Our vision: autonomous infrastructure for sustained business performance. Combining AIOps with generative AI, we're designing systems from day one for security, scalability, and production readiness.

Role Overview

We seek a Senior AI Engineer or Research Scientist with hands-on experience in developing and deploying AI/ML systems at scale. Your contributions will drive BugRaid.AI's agentic intelligence, enabling our platform to conduct root cause analysis (RCA) and automated remediation in demanding environments.

This position bridges AI research and production engineering. You'll experiment with LLMs, reinforcement learning, and synthetic data, then implement these concepts into scalable, dependable systems.

Key Responsibilities

  • Enterprise-Ready AI Development: Design, implement, and deploy AI agents that operate reliably under enterprise constraints, such as multi-cloud environments, zero-data egress, and compliance requirements.
  • LLM & Agent Research: Develop and test reasoning workflows, prompting strategies, and tool-use policies tailored for large-scale observability data.
  • Training & Alignment: Utilize techniques like fine-tuning, RLHF, and reward modeling to ensure AI behavior aligns with real SRE workflows, avoiding toy datasets.
  • Synthetic Data Generation: Create scalable pipelines for producing synthetic incidents—logs, metrics, traces—used for training and benchmarking in scenarios with limited data.
  • Cross-Team Collaboration: Collaborate closely with infrastructure engineers, SREs, and product leaders to incorporate AI research into the BugRaid.AI platform.
  • Production Excellence: Design systems with built-in observability, monitoring, and CI/CD processes, ensuring failover, rollback, and resilience capabilities.
  • Frontier Tracking: Keep up with the latest research in LLMs, agentic AI, and reliability, incorporating innovations into enterprise production environments.

Requirements

  • 5+ years of production experience building and deploying ML/AI systems at scale.
  • PhD or Master's in Computer Science, Machine Learning, or related fields (or equivalent experience).
  • Strong foundation in deep learning, reinforcement learning, or robotics.
  • Hands-on experience with LLM fine-tuning, RLHF, or synthetic data generation.
  • Proven track record of shipping AI systems into production (not just research prototypes).
  • Experience with cloud-native architectures (AWS/Azure/GCP), Kubernetes, and MLOps tooling (SageMaker, MLflow, Ray, Kubeflow).
  • Comfort working with large-scale data streams (Kinesis, Kafka, Flink) and vector databases (OpenSearch, Pinecone, Weaviate).
  • Strong collaboration skills and ability to communicate across research, engineering, and product teams.

Benefits

  • Work on high-impact AI challenges that sit at the intersection of AI, DevOps, and enterprise reliability.
  • Shape the core intelligence layer of a product designed to be enterprise-ready from day one.
  • Collaborate with a world-class founding team experienced in AI, DevOps, and large-scale systems.
  • Competitive compensation and a chance to join at an early stage with an outsized impact.
  • A culture that values research rigor, engineering excellence, and execution speed.

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