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.