AI Architect (Wealth) in London

This position is pivotal in designing AI and Machine Learning solutions on cloud-based platforms, exploring emerging AI trends, developing proof-of-concepts, and collaborating with internal and external ecosystems to advance these concepts to production.

The role demands expertise in designing AI platforms and governance frameworks, with delivery experience in regulated environments.

• Consume, integrate, and operationalise advanced AI models, including Large Language Models (LLMs) and Small Language Models, into secure, governed, and scalable business solutions.
• Enforce data-handling policies in code, utilising prompt redaction middleware, retrieval allow-lists, and per-use-case policies.
• Add evaluation gates for answer quality and safety in pipelines, implement canary deployments with feature flags, and automate rollbacks on drift.
• Manage the lifecycle of models, including fine-tuning with consented datasets, synthetic augmentation policies, and maintaining model registry entries with lineage.
• Implement tracing for observability, manage latency and cost SLOs, and set alerts for hallucination and safety incidents.
• Develop provider abstractions for OpenAI, Gemini, Azure OpenAI, and Vertex, including capturing provider/region, model/version, and quota routing.
• Schedule index rebuilds, freshness windows, incremental sync, and manage search quality dashboards with regression alerts.
• Develop APIs and microservices to integrate AI with internal and external applications.
• Partner with business stakeholders to identify and validate use cases.

• At least 6-10 years of hands-on development and architectural experience.
• Proficiency in Python, PyTorch, TensorFlow, or similar frameworks.
• Experience with supervised, unsupervised, and reinforcement learning.
• Solid grounding in Natural Language Processing (NLP) concepts such as tokenisation, embeddings, semantic search, text classification, and summarisation.
• Strong understanding of Large Language Models (LLMs) and Generative AI (GAI), with hands-on experience in LangGraph, LlamaIndex, OpenAI APIs, and Model Context Protocol (MCP).
• Knowledge of statistics, probability, and model evaluation techniques.
• Experience with Retrieval-Augmented Generation (RAG) and vector databases like Pinecone or Weaviate.
• Proven track record of designing, developing, deploying, and managing AI/GenAI solutions in production.

• A broader understanding of machine learning algorithms.
• Exposure to multimodal AI (text vision, speech).
• Data engineering and analysis skills including ETL pipelines and feature engineering.
• Familiarity with MLOps/DevOps pipelines, monitoring, and retraining.
• Understanding of knowledge graphs, embeddings optimisation, and enterprise search integration.
• Strong collaboration and communication skills to work with cross-functional teams.

• Enjoy the flexibility of a hybrid work environment with 1-3 days per week in London, along with opportunities to travel to India once a month.
• Experience a dynamic and collaborative workplace that values innovation and professional growth.

• The role offers a hybrid work model with 1-3 days per week in London.
• It involves travel to India once per month.
• The workplace fosters a dynamic environment, utilising cutting-edge technologies and frameworks such as AWS, GCP, Azure, Git, Docker, Kubernetes, and CI/CD for ML workflows.
• The position requires a professional dress code conducive to business interactions.