NetEnrich Technologies
4 weeks ago
Job Description :
Netenrich boosts the effectiveness of organizations' security and digital operations so they can avoid disruption and manage risk. Resolution Intelligence CloudTM is our native-cloud data analytics platform for enterprises and services providers that need highly scalable, multitenant security operations and/or digital operations management.
Resolution Intelligence Cloud transforms security and operations data into intelligence that organizations can act on before critical issues occur. More than 3,000 customers and managed service providers rely on Netenrich to deliver secure operations at scale.
Role : LLM (Python, AI/ML)
Experience : 2+Yrs
Location : Hyderabad
Role :
We are seeking an LLM Engineer with a focus on working with Large Language Models (LLMs) to create agents, tools, and multi-agent systems that enhance and converge Digital and Security Operations. You will be responsible for developing tools that connect to data sources, and integrating third-party systems. The role includes working with semantic storage and RAG (Retrieval-Augmented Generation) techniques
Job Responsibilities :
- Develop and deploy LLM-driven agents to automate tasks in Digital and Security Operations, such as vulnerability detection, compliance enforcement, and threat response
- Work and integrate with technologies like LangChain, Hugging Face, OpenAI API, Anthropic (Claude), Cohere, and Google Gemini
- Build and optimize tools that connect to various data sources and integrate with third-party systems for seamless data flow and interaction
- Write and apply different prompt engineering techniques (Self-consistency , ReAct, Few-shot STAR, AutoPrompt) for various tasks, optimizing LLM behaviour for specific use cases
- Create and manage multi-agent systems that improve collaboration between agents for operational and security improvements
- Integrate LLM models with platforms like SIEM, SOAR, and other tools to enhance security monitoring, threat detection, and automation workflows
- Utilize semantic storage tools like FAISS , Pinecone to implement retrieval-based techniques and optimize search and information retrieval
Required Skills :
- 2 to 3 years of experience working specifically with LLMs in AI/ML environments.
- Proficiency in Python for developing LLM-driven solutions
- Expertise in various prompt engineering techniques
- Hands-on experience with semantic storage and vector databases (e.g., FAISS , Pinecone) and using RAG techniques to enhance LLM capabilities
- Expertise in writing various types of prompt engineering techniques for optimizing LLM responses and behavior
- Hands-on experience with a focus on connecting to data sources and third-party integrations
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