Overview
Enterprise Applied AI Solutions Engineer focused on implementing agentic and generative AI features for internal workflows and employee productivity.
What you'll do
- Build and enhance AI-powered features such as copilots, summarization, classification, routing, and Q&A.
- Partner with business users to clarify requirements, run demos, capture feedback, and iterate toward measurable outcomes.
- Develop knowledge-based agents using Retrieval-Augmented Generation (RAG) patterns and improve retrieval quality.
- Design conversational flows for internal functions, including intent handling, escalation paths, and handoff to human support.
- Implement simple agentic or predictive models for operational use cases (e.g., predicting customer support ticket volume) under guidance.
- Manage an AI feature backlog, write user stories, define acceptance criteria, coordinate UAT, and support evaluation/regression testing.
What you'll need
- 3+ years of experience in software engineering or applied solutions development.
- Proficiency in Python and API-based integration.
- Working knowledge of SQL and data access patterns.
- Working familiarity with LLMs, prompt engineering, and RAG.
- Exposure to agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and tool/function calling patterns.
- Basic understanding of enterprise security, privacy, and data governance guardrails.
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
Details
- Location: Bangalore, India.
Read the full description and apply on the company’s own careers page.
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