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Senior AI Engineer
4 weeks ago
Company Description
BugRaid.AI harnesses advanced AIOps and AI bots to proactively manage and respond to incidents, revolutionizing the entire process. Our innovative solution integrates comprehensive incident analysis with real-time response capabilities, distinguishing us within the industry. We expedite resolution by swiftly identifying and addressing issues to minimize downtime and improve efficiency. Our platform is engineered for scalability and flexibility, providing in-depth insights through comprehensive analytics to support informed decision-making.
Role Description
This is a full-time remote position for a Senior AI Engineer. The Senior AI Engineer will be responsible for designing, developing, and optimizing AI systems focused on AWS, Large Language Models (LLMs), Generative AI (GenAI), Agentic AI, and AIOps. Responsibilities include building and deploying AI models, analyzing their performance, and integrating AI solutions with existing systems.
Responsibilities
- Design Agentic Systems: Develop and enhance multi-step reasoning agents that operate with live infrastructure and observability data (logs, metrics, traces).
- Develop Real-World GenAI Applications: Incorporate LLMs into production environments demanding low latency and high availability.
- Prompt Engineering & Orchestration: Create tools for function calling, agent workflows, and dynamic prompt tuning.
- Conduct Experiments & Deployment: Rapidly prototype, evaluate, and refine LLMs, agent workflows, and evaluation mechanisms.
- Monitor & Assess: Establish observability and continuous evaluation pipelines to ensure the reliability of AI agents in practical scenarios.
- Foster Collaboration: Work closely with the backend, infrastructure, and product teams to embed AI agents within the core BugRaid system.
Qualifications
- Over 3+ years of experience in software engineering, preferably within AI/ML, GenAI, or data engineering roles.
- Proficiency in Python and its machine learning/AI ecosystem.
- Hands-on experience with AWS, LLMs, or agent frameworks such as LangChain, LangGraph, CrewAI, etc..
- Familiarity with observability data and incident troubleshooting workflows.
- Practical experience in developing distributed systems, data pipelines, or real-time machine learning infrastructure.
- Demonstrated initiative and capability to transition ideas from prototypes to production environments.
Additional Considerations:
- Experience with model fine-tuning, RLHF, or contributions to open-source AI agents.
- Knowledge of AWS, Azure, Terraform, Kubernetes, or platforms for ML orchestration.
- Contribution to or development of large-scale GenAI platforms or systems ensuring AI reliability.
Perquisites & Benefits
- Culture emphasizing remote work (within India), supported by team hubs located in Hyderabad and Bangalore.
- Competitive startup compensation complemented by generous Employee Stock Ownership Plans (ESOPs) – emphasizing ownership.
- Collaboration with passionate engineers, AI specialists, and DevOps leaders from leading organizations.
- Significant opportunity to create impactful AI products that transform global infrastructure operations.
