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Protocol Intelligence
Data-driven signals on your job's competitivenessKnown fintech brand and Bangalore metro increase applicants, but specialized LLM skills moderately limit competition.
LLM engineering skills are broadly transferable across industries despite some enterprise governance nuances.
Many mandatory LLM, LangChain, vector DB, cloud deployment, and AI security requirements make shortlisting stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Design and deploy end-to-end production-grade AI agents using large language models integrated into applications.
Develop AI architecture patterns (e.g., RAG, text-to-SQL, multi-agent) and maintain AI workflows and pipelines using frameworks like LangChain or LangGraph.
Implement secure, compliant AI systems with monitoring, observability, automated deployment (CI/CD), and tool orchestration across enterprise services.
Minimum Requirements
Strong proficiency in Python for AI/ML development.
Hands-on experience with AI frameworks like LangChain, LangGraph, CrewAI, or equivalent.
Understanding of LLM fundamentals, prompt engineering, AI agent design patterns, and vector databases (e.g., Pinecone, Weaviate).
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in building secure, enterprise-grade AI solutions with data governance, compliance, and cybersecurity (including prompt injection risk mitigation).
Familiarity with cloud deployment of LLMs on platforms such as Azure OpenAI or AWS Bedrock and using CI/CD for model deployment automation.
Proficient in AI system observability, monitoring, and using Model Context Protocol (MCP) or similar orchestration frameworks for scalable multi-agent AI workflows.