AI Systems Engineer

7 days ago

Thrissur, Kerala, India beBeeArtificial Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Summary

We are seeking an accomplished AI professional with a strong background in developing and deploying intelligent systems at scale.

The ideal candidate will have a proven track record of shipping reliable and scalable AI solutions into production, with expertise in LLMs, reinforcement learning, and synthetic data generation.

This is an exceptional opportunity to join a dynamic team and contribute to the development of cutting-edge AI technologies that drive business success.

Responsibilities

  • 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 specifically tailored for large-scale observability data.
  • Training & Alignment: Utilize techniques such as fine-tuning, RLHF, and reward modeling to ensure AI behavior aligns with real SRE workflows, thereby avoiding reliance on 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 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, and incorporate these innovations into production environments.

Requirements

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

Benefits

  • High-Impact Work: Contribute to high-impact AI challenges that sit at the intersection of AI, DevOps, and enterprise reliability.
  • Culture: Join a culture that values research rigor, engineering excellence, and execution speed.
  • Compensation & Equity: Competitive compensation, equity (ESOPs), and a chance to join at an early stage with an outsized impact.

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