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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer and Bengaluru location increase applicant density, but niche LLM+fullstack skills moderate competition.
LLM, RAG, and fullstack expertise are specialized but broadly transferable across industries.
Explicit 6–8 years, 1–2 years GenAI, and specific tech stack make filtering stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and scale AI-powered applications using Large Language Models, agentic workflows, and Retrieval-Augmented Generation with enterprise knowledge sources.
Develop full stack solutions including responsive frontends, scalable backend APIs, and cloud-native AWS deployments with CI/CD, containerization and orchestration.
Integrate AI services with business applications ensuring system security, reliability, and production readiness.
Minimum Requirements
6-8 years of software engineering experience with at least 1-2 years of Generative AI practical experience.
Strong proficiency in Python and React with cloud experience (AWS preferred), including production deployment skills.
Experience with AI frameworks and tools such as LangGraph, LangChain, LlamaIndex, and AI service integrations (OpenAI, Anthropic, Bedrock, Azure OpenAI).
Ability to work independently across the full technology stack including frontend, backend, AI integration, cloud infrastructure, and databases (SQL/NoSQL).
Ideal Candidate Profile
Experienced full stack engineer with deep expertise in generative AI technologies and deployments to production environments.
Skilled in building scalable, reusable AI solutions that support multiple business teams and improve developer productivity through automation.
Familiar with AI observability, agentic AI workflows, vector databases, and enterprise tool integrations (e.g., Microsoft Teams, Jira, ServiceNow).