Artificial Intelligence Engineer

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 actions—like 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 2–3+ 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/DB’s.
• 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