AI System Architect

2 days ago

Amrāvati, Maharashtra, India beBeeArtificialIntelligence Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Transforming AI Expertise into Production Excellence

We are seeking a highly skilled individual to drive the development and deployment of cutting-edge AI/ML systems at scale. Your contributions will enable our platform to conduct root cause analysis and automated remediation in demanding enterprise settings.

This role bridges AI research and production engineering, requiring experimentation with large language models, reinforcement learning, and synthetic data. You will implement these concepts into enterprise-grade, scalable, and dependable systems.

Key Responsibilities

  • Design, implement, and deploy AI agents that operate reliably under enterprise constraints, including multi-cloud environments, zero-data egress, and compliance requirements.
  • Develop and test reasoning workflows, prompting strategies, and tool-use policies tailored for large-scale observability data.
  • Utilize techniques such as fine-tuning, RLHF, and reward modeling to ensure AI behavior aligns with real SRE workflows.
  • Create scalable pipelines for producing synthetic incidents—logs, metrics, traces—used for training and benchmarking.
  • Cross-Team Collaboration: Work closely with infrastructure engineers, SREs, and product leaders to incorporate AI research into our platform.
  • Production Excellence: Design systems with built-in observability, monitoring, and CI/CD processes, ensuring failover, rollback, and resilience capabilities.
  • Frontier Tracking: Stay up-to-date with the latest research in LLMs, agentic AI, and reliability, and apply these innovations into enterprise production environments.

Essential Skills and Qualifications

  • 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.
  • Experience with cloud-native architectures, Kubernetes, and MLOps tooling.
  • Comfort working with large-scale data streams and vector databases.
  • Strong collaboration skills and ability to communicate across research, engineering, and product teams.

Nice to Have

  • Background in observability or large-scale production debugging.
  • Experience designing secure AI systems.
  • Contributions to open-source agent frameworks.
  • Experience with real-time ML serving.
  • Prior experience in enterprise SaaS or reliability-focused products.

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