AI engineer Lead

Role Overview:
We are looking for an AI Technical Lead to define and drive the end-to-end AI architecture, including enterprise-scale
product development, vector search, and generative AI applications. This role will own the design, implementation,
and optimization of intelligent systems that operate over a large enterprise corpus.

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.

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.