AI Engineer | Immediate | Hybrid | 5+ Yrs
Posted Updated 1
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Summary
Senior AI Engineer (Bengaluru, hybrid) building production GenAI applications: smart catalogue search & recommendations, agentic chat that triggers real workflows (POs, compliance checks), and call-transcript summarization, integrated with ERPs like NetSuite. Core stack: Python/FastAPI, vector DBs, LangChain/LangGraph, OpenAI/Anthropic/Gemini APIs.
Role Summary
We Are Looking For a experienced Senior AI Engineer who is strong in Generative AI skills to build real, working business applications. This is not just tweaking prompts, rather connecting smart AI features into client's existing software, databases, and daily workflows.
Key Responsibilities
- Smart Catalogue Search & Recommendations: Build a search and recommendation engine that can navigate millions of product variations (like 50,000+ types of office furniture) and help users find exact, compliant items quickly.
- Interactive AI Chat & Automation: Create an AI chat interface that doesn't just answer questions, but takes actual actionslike creating Purchase Orders (POs), triggering compliance checks, and updating core backend systems.
- Design an Actionable Agentic Chat Interface capable of initiating enterprise workflows
- Call Transcript Summarization: Build pipelines to process, clean, and summarize long customer call transcripts so key details are captured automatically.
- Integration & Backend Work: Connect these AI tools into existing company platforms (including ERP systems like NetSuite) so everything runs seamlessly behind the scenes.
- Build Intelligent Recommendation Engine
Must-Have Experience
- 5 to 7 years of total software development experience, with at least 23+ years directly hands-on with GenAI, Large Language Models (LLMs), and production AI engineering.
- Proficiency in Python: Advanced mastery of core backend development (FastAPI, Flask, AsyncIO), REST APIs, and microservices architecture.
- Vector Databases & Search: Proven experience with vector engines/DBs.
- Agentic Frameworks & LLM Stack: Hands-on experience with LangChain, LlamaIndex, LangGraph, or CrewAI for multi-step reasoning, memory retention, and tool calling.
- Model APIs & Orchestration: Direct integration experience with major foundation model APIs (OpenAI, Anthropic, Google Gemini, Hugging Face).
- Enterprise Integration: Experience connecting AI services to ERP systems (NetSuite, SAP), custom backends, and external third-party software.
- Collaborative Filtering / Hybrid ML vs. LLM-based Reranking
