Roles & Responsibilities:

• Implement the AI strategy and architecture for the platform.
• Build and scale indexing, search, and summarization pipelines.
• Design RAG-based systems for contextual document retrieval and insights.
• Optimize system performance to meet strict latency and quality SLAs.
• Establish AI evaluation, monitoring, and feedback loops for continuous improvement.
Mandatory Skills
• Strong experience designing and deploying LLM-based systems (RAG, summarization, classification,
extraction).
• Hands-on expertise with LLM orchestration frameworks (LangChain, LlamaIndex, or equivalent).
• Deep understanding of prompt engineering, evaluation, and model tuning strategies.
• Proven experience building large-scale search systems using vector search + keyword (hybrid search).
• Hands-on experience with Azure AI Search / OpenSearch / Elasticsearch with embeddings.




• Expertise in indexing pipelines, document chunking, ranking, and relevance tuning.
• Strong foundation in NLP techniques (NER, classification, summarization, semantic similarity).
• Experience using transformer models (Hugging Face, OpenAI, etc.) in production.
• Ability to design systems for continuous learning from user feedback.

Valuable to have Skills:

• Experience on developing M365 Copilot Studio agents with multiple knowledge base. Familiarity with Power
Automate & Power Apps integration with Agents.
• Understanding of caching strategies, embedding management, and cost optimization.
• Ability to define AI architecture roadmap aligned with product goals.
• Exposure to fine-tuning or customization of models.

📌 AI Technical Lead (Noida)
🏢 Talentoj
📍 Noida