Senior AI Engineer - BugRaid AI

Location: Hyderabad/Bangalore/Singapore

About BugRaid.AI

Incidents are the silent killers of modern enterprises. Every minute of downtime means lost revenue, lost trust, and engineers under fire.

world’s first enterprise-ready incident copilot

autonomous reliability for enterprise infrastructure

Role Overview

Senior AI Engineer

AI research and production engineering

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 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 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, and incorporate these 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

  .

Nice to Have

• Background in

  observability (logs, metrics, traces)

  or large-scale production debugging.
• Experience designing

  secure AI systems

  (data privacy, zero-data egress, compliance frameworks like HIPAA/FedRAMP).
• Contributions to

  open-source agent frameworks

  (LangChain, LlamaIndex, Haystack, Ray Serve).
• Experience with

  real-time ML serving

  (low-latency inference, batch + streaming pipelines).
• Prior experience in

  enterprise SaaS

  or reliability-focused products.

Why Join BugRaid.AI

• 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,

  equity (ESOPs)

  , and a chance to join at an

  early stage

  with an outsized impact.
• A culture that values

  research rigor, engineering excellence, and execution speed

  .