We have a new requirement for an Ai Architect to work for a client of ours.

This role has been deemed as Inside IR35.

Experience required:
- Ai Architecture
- Ideally financial service background
- ability to manage stakeholders (translate technical information for non-technical stakeholders)

Essential AI Design and Architecture Skills
* Prompt Engineering: Crafting structured prompts to drive deterministic and reproducible outputs from LLMs, using techniques like chain-of-thought and few-shot prompting
* Context Engineering: Dynamically injecting relevant external data into prompts; designing and managing context windows, handling retrieval noise and context collapse in long-context
* Fine-Tuning & Model Adaptation: Using methods like LoRA/QLoRA for domain adaptation, managing data curation pipelines, and monitoring overfitting versus generalization-especially in high-stakes environments
* Retrieval-Augmented Generation (RAG): Building LLM workflows with external knowledge integration, engineering embeddings and retrieval pipelines for high recall and precision
* Agentic Design: Orchestrating LLM-driven agents capable of multi-step reasoning, tool use, and autonomous state management-including fallback strategies for error
* Production Deployment: Packaging models and agentic systems as scalable APIs, with robust pipelines for latency, concurrency, and failure isolation, including container orchestration or serverless deployment
* LLM Optimization: Applying quantization, pruning, and distillation to optimize performance and cost; benchmarking for speed, accuracy, and hardware utilization
* Observability & Monitoring: Implementing logging, tracing, dashboards, and alignment monitoring for prompts, responses, and agent behaviors
* Core SDLC AI Integration: Using generative AI for requirement refinement, technical design blueprinting, architecture review, API and schema auto-generation, and cross-functional artifact production
* Security & Compliance: Building guardrails to enforce data privacy, compliance with regulations, and responsible use of LLMs, particularly in sensitive or regulated environments.
* Modern Deep Learning: Mastery of frameworks including TensorFlow, PyTorch, and HuggingFace Transformers, with proven expertise in transformers, CNNs, RNNs, and attention mechanisms for custom and state-of-the-art model

To be considered please submit an up-to-date CV.
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