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.
- Solid 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.

Good 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