Job
Description
As an experienced AI/ML Engineer in our company, your role will involve designing and implementing intelligent systems using large language models (LLMs) for observability and operational workflows. You will focus on building AI-driven solutions for anomaly detection, alert triage, and automated root cause analysis in production environments. **Key Responsibilities:** - **LLM Development & Deployment** - Design and deploy large language model solutions using Ollama, AWS Bedrock, or similar platforms - Implement agentic networks and multi-agent systems for complex operational workflows - Develop context-based prompt engineering strategies for production LLM applications - Fine-tune and optimize LLMs using LoRA (Low-Rank Adaptation) techniques - Integrate Model Context Protocol (MCP) for enhanced agent communication - **Observability & Operations** - Build AI-driven observability workflows for monitoring and operational intelligence - Design and implement intelligent alerting systems that reduce noise and improve signal quality - Develop automated alert triage mechanisms using ML-based classification - Create root cause analysis systems that leverage LLMs for faster incident resolution - Integrate LLM capabilities into existing operational pipelines and monitoring infrastructure - **System Integration & Optimization** - Develop robust APIs and integrations for LLM-powered features - Optimize model performance for latency-sensitive operational use cases - Implement monitoring and evaluation frameworks for LLM outputs - Build feedback loops to continuously improve model accuracy and relevance **Required Qualifications:** - **Technical Skills** - Programming: Strong proficiency in Python with experience in production-grade code - ML Frameworks: Hands-on experience with PyTorch, TensorFlow, LangChain, or similar frameworks - LLM Deployment: Practical experience deploying LLMs using platforms like Ollama, AWS Bedrock, OpenAI API, Anthropic Claude API, or similar - Prompt Engineering: Proven ability to design effective prompts and context strategies - Version Control: Git/GitHub proficiency - **AI/ML Experience** - 3+ years of experience in machine learning or AI engineering - Demonstrated experience working with large language models in production - Understanding of transformer architectures and attention mechanisms - Experience with model evaluation, testing, and performance optimization - Familiarity with vector databases and semantic search (Pinecone, Weaviate, ChromaDB, etc.) - **System Architecture** - Experience building scalable ML systems and APIs - Understanding of microservices architecture and containerization (Docker, Kubernetes) - Familiarity with cloud platforms (AWS, GCP, or Azure) - Knowledge of CI/CD pipelines for ML models **Additional Details:** This section is omitted as there are no additional details about the company mentioned in the job description provided. This Full-time role offers benefits including food provision, health insurance, life insurance, paid sick time, and paid time off. If you join us, you will work on near-term projects such as deploying LLM-powered alert triage systems, building intelligent incident summarization using context-aware prompts, implementing anomaly detection for production metrics using ML models, and creating automated root cause analysis workflows. In the long term, you will be involved in developing self-healing systems that use LLMs for autonomous remediation, building predictive models for proactive issue detection, creating natural language interfaces for operational queries, and designing multi-agent systems for complex operational decision-making.,
