AI Architect

We are seeking a Senior AI Engineer to lead the technical delivery of an intelligent document processing platform. This role combines technical leadership with hands-on engineering. You will define the AI processing strategy, guide the engineering team, and be accountable for the quality and scalability of the platform across a large corpus of enterprise documents.

Key Responsibilities :

• Own the end-to-end AI architecture across ingestion, classification, extraction, indexing, and retrieval.

• Define the hybrid AI strategy — determining when to use deep learning models, traditional NLP, and LLMs.

• Make architectural decisions on model routing, chunking strategies, and cost-quality trade-offs at scale.

• Define the information extraction framework, confidence scoring model, and output structure.

• Lead the vector indexing and RAG retrieval layer, including embedding models and semantic search tuning.

• Guide and mentor AI Engineers — reviewing code, setting standards, and providing technical direction.

• Collaborate with the Full-Stack Developer on API contracts and pipeline output integration.

• Drive performance optimisation, error handling, and fallback mechanisms across the pipeline.

• Produce technical documentation and handover materials.

• Serve as the primary technical point of contact with client stakeholders.

**Required Skills:**

• 6+ years of experience in AI/ML engineering, with at least 1 year in a senior or architect-level role.

• Deep expertise in Python 3 and the modern AI/NLP stack.

• Proven experience deploying production AI pipelines on Azure.

• Strong understanding of LLM orchestration, prompt engineering, RAG architecture, and embedding strategies.

• Experience with hybrid AI approaches combining deep learning, traditional NLP, and LLMs.

• Experience processing large corpora of heterogeneous documents at scale.

• Experience navigating enterprise cloud environments with security and compliance constraints.

• Track record of mentoring engineers and maintaining engineering standards.

Preferred  Qualifications:

• Experience with enterprise document repositories and their integration APIs.

• Familiarity with Azure AI Studio and custom model deployment.

• Exposure to distributed processing frameworks for large-scale batch operations.

• Strong communication skills for client-facing technical discussions.